The document provides an overview of emojis including their history, how they work technically using unicode, code examples in JavaScript, and diversity and inclusion related to emojis. It discusses emoji modifiers, zero-width joiner sequences, and ways brands are using emojis in marketing. Useful links are provided about emoji domains, conferences, tracking usage, and products/tools related to emojis.
This document discusses emoji and the author's favorite emoji. It mentions dab+emoji and provides details about Season 1, Episode 5 of the TV show "Nailed it!" along with the hashtag #GoCubs!.
Emotion recognition using image processing in deep learningvishnuv43
User’s emotion using its facial expressions will be detected. These expressions can be derived from the live feed via system's camera or any pre-existing image available in the memory. Emotions possessed by humans can be recognized and has a vast scope of study in the computer vision industry upon which several researches have already been done.
We propose a compact CNN model for facial expression recognition.
The work has been implemented using Python Open Source Computer Vision Library (OpenCV) and NumPy,pandas,keras packages. The scanned image (testing dataset) is being compared to training dataset and thus emotion is predicted.
This document describes a sign recognition system to translate sign language gestures from deaf and dumb people into audible speech. The system uses Harris corner detection and SIFT to extract features from captured images of gestures. K-nearest neighbors algorithm is used to match features to a database of images and identify the sign. A serial board communication kit then converts the text result to speech using a text-to-speech module and speaker. Examples show the system correctly identifying the signs for letters A, B, and C from captured images.
Emotion Detection using Artificial Intelligence presentation by Aryan Trisal.
In this ppt you will learn about emotion detection using AI and how will it change the world.
IF U WANT A PPT MADE AT VERY LOW PRICES CONTACT ME ON LINKEDIN -www.linkedin.com/in/aryan-trisal-420253190
Facial emotion recognition uses active shape modeling to identify 5 classes of emotions from facial images. It reconstructs facial models by labeling landmark features, performing shape modeling through principal component analysis and model fitting, and classifying emotions. The methodology was tested on a set of labeled images and achieved over 80% accuracy in emotion recognition according to the results.
This document describes an emotion-based music player that generates playlists based on a user's detected mood. It uses three main modules: an emotion extraction module that analyzes facial expressions from webcam images to determine mood, an audio feature extraction module that extracts data from songs, and an emotion-audio recognition module that maps the facial and audio features to select songs for the playlist. The system aims to reduce the effort of manually creating playlists by automatically generating ones tailored to the user's current emotional state. It works by classifying facial expressions and songs into categories like happy, sad, and angry to create playlists that match or influence the user's detected mood.
This document provides information about the Unit Converter Android application. It discusses that Android is a software stack for mobile devices that includes an operating system and applications. It also describes that an Android application runs on the Android platform, typically on a smartphone or tablet. The document outlines that the primary objective of the Unit Converter app is to allow users to convert various units, including length, temperature, currency, and weight. It was developed in Java using the Android Studio IDE. It provides descriptions of key aspects of the app, including activities, splash screens, toasts, spinners, layout files, EditText fields, and key methods like onCreate() and findViewById(). Screenshots of the app interface are also included.
This document describes various algorithms used to build a facial emotion recognition system, including Haar cascade, HOG, Eigenfaces, and Fisherfaces. It explains how each algorithm works, such as how Haar cascade detects facial features and HOG extracts histograms of gradients. The system is trained on the CK+ dataset and uses Eigenface and Fisherface classifiers to classify emotions, achieving higher accuracy (86.54%) with Fisherfaces. It provides code snippets of key steps like cropping, resizing images, splitting data, and predicting emotions.
This document discusses emoji and the author's favorite emoji. It mentions dab+emoji and provides details about Season 1, Episode 5 of the TV show "Nailed it!" along with the hashtag #GoCubs!.
Emotion recognition using image processing in deep learningvishnuv43
User’s emotion using its facial expressions will be detected. These expressions can be derived from the live feed via system's camera or any pre-existing image available in the memory. Emotions possessed by humans can be recognized and has a vast scope of study in the computer vision industry upon which several researches have already been done.
We propose a compact CNN model for facial expression recognition.
The work has been implemented using Python Open Source Computer Vision Library (OpenCV) and NumPy,pandas,keras packages. The scanned image (testing dataset) is being compared to training dataset and thus emotion is predicted.
This document describes a sign recognition system to translate sign language gestures from deaf and dumb people into audible speech. The system uses Harris corner detection and SIFT to extract features from captured images of gestures. K-nearest neighbors algorithm is used to match features to a database of images and identify the sign. A serial board communication kit then converts the text result to speech using a text-to-speech module and speaker. Examples show the system correctly identifying the signs for letters A, B, and C from captured images.
Emotion Detection using Artificial Intelligence presentation by Aryan Trisal.
In this ppt you will learn about emotion detection using AI and how will it change the world.
IF U WANT A PPT MADE AT VERY LOW PRICES CONTACT ME ON LINKEDIN -www.linkedin.com/in/aryan-trisal-420253190
Facial emotion recognition uses active shape modeling to identify 5 classes of emotions from facial images. It reconstructs facial models by labeling landmark features, performing shape modeling through principal component analysis and model fitting, and classifying emotions. The methodology was tested on a set of labeled images and achieved over 80% accuracy in emotion recognition according to the results.
This document describes an emotion-based music player that generates playlists based on a user's detected mood. It uses three main modules: an emotion extraction module that analyzes facial expressions from webcam images to determine mood, an audio feature extraction module that extracts data from songs, and an emotion-audio recognition module that maps the facial and audio features to select songs for the playlist. The system aims to reduce the effort of manually creating playlists by automatically generating ones tailored to the user's current emotional state. It works by classifying facial expressions and songs into categories like happy, sad, and angry to create playlists that match or influence the user's detected mood.
This document provides information about the Unit Converter Android application. It discusses that Android is a software stack for mobile devices that includes an operating system and applications. It also describes that an Android application runs on the Android platform, typically on a smartphone or tablet. The document outlines that the primary objective of the Unit Converter app is to allow users to convert various units, including length, temperature, currency, and weight. It was developed in Java using the Android Studio IDE. It provides descriptions of key aspects of the app, including activities, splash screens, toasts, spinners, layout files, EditText fields, and key methods like onCreate() and findViewById(). Screenshots of the app interface are also included.
This document describes various algorithms used to build a facial emotion recognition system, including Haar cascade, HOG, Eigenfaces, and Fisherfaces. It explains how each algorithm works, such as how Haar cascade detects facial features and HOG extracts histograms of gradients. The system is trained on the CK+ dataset and uses Eigenface and Fisherface classifiers to classify emotions, achieving higher accuracy (86.54%) with Fisherfaces. It provides code snippets of key steps like cropping, resizing images, splitting data, and predicting emotions.
In this tutorial, you will learn the basics of scripting in Unity by:
- Creating a new script component and adding it to a GameObject
- Exploring the default script structure and functions like Start and Update
- Adding a variable to the script and editing its value in the Inspector
- Using Debug.Log to output messages to the Console
- Changing a property of a GameObject by editing values in the script
This document presents an overview of a calculator application called "My Calculator". It discusses the features of the calculator, which include standard calculation functions, scientific calculations, unit conversion, GPA calculation, and solving mathematical problems. The document also provides information on the project status, implementation details using Java libraries and classes like Swing, JFrame and ActionListener. It was presented by three individuals and details the progress made on developing the calculator application.
This document summarizes face recognition techniques. It discusses three levels of facial details, from gross to micro features, and how they require different image resolutions. It also outlines the major components of a face recognition system: image acquisition, face detection, and face matching. Finally, it describes common image formats like 2D photos and 3D scans, and detection methods like Viola-Jones that use Haar-like features and AdaBoost training.
It's a new Windows based application for visually impaired person..!
This application will provides only, mail services for blinds and there's no voice duplications allowed during the user login.
This document outlines a project to design and develop a Sugar CRM bot using Artificial Intelligence Markup Language (AIML). The objective is to create a bot that can answer questions about Sugar CRM. It will be implemented as both a desktop and web application using programming languages like AIML, Python, and Adobe Flex. An automatic AIML generation tool will also be developed to ease the creation of AIML files. The source code for the project is available online for checkout and demonstration.
Emotion detection from text using data mining and text miningSakthi Dasans
Emotion detection from text using data mining and text mining
Based on research paper published by Faculty of Engineering, The University of Tokushima at IEEE 2007 we build an intelligent system under the title Emotelligence on Text to recognize human emotion from textual contents.
i.e. if you give an input string , our system would possibly able to say the emotion behind that textual content.
Complete power point presentation on SPEECH RECOGNITION TECHNOLOGY.
Very helpful for final year students for their seminar.
One can use this presentation as their final year seminar.
Speech Recognition is a very interesting topic for seminar.
This document presents a human emotion recognition system that uses facial expression analysis to identify emotions. It discusses how emotions are important to human life and interaction. The system first captures images of a human face and preprocesses the images to extract features. It then compares the facial features to examples in a database to recognize the emotion based on distances between features. The system can identify six basic emotions with up to 97% accuracy. Limitations and potential to incorporate fuzzy logic for improved classification are also discussed.
In the era of technology, the voting machine, which is present today, is highly unsecured. Being in the age of Computers we are compromising the security by opting for Electronic voting machine because in the present electronic voting machine is not intelligent that is it cannot determine the person came for the voting is eligible or not . That mean the whole control is kept in the hand of voting in charge officer. One more risk with the present voting machine is that anybody can increase the vote count, since the count is present in the machine itself.
In proposed machine that is “Global Wireless E-Voting” , The machine is made intelligent which can determine the eligibility of the voter by scanning the eye pattern and also the vote count is not kept into the same machine itself instead of it it is store in the remote server by converting it into radio waves. Here there is no chance of increasing the vote count of machine. Even in case of damage to voting machine there will not be harm to continuity of the election process. The machine provides high level of security, authentication, reliability, and corruption -free mechanism. By this we can get result within minute after a completion of voting. Minimum manpower Utilization, hence mechanism is error free.
Global Wireless E-Voting is an intelligent system which can determine the eligibility of the voter by scanning the eye pattern and also the vote count is not kept into the same machine itself instead of it is store in the remote server by converting it into radio waves.
.
The machine provides high level of security, authentication, reliability, and corruption -free mechanism. Here there is no chance of increasing the vote count of machine. Even in case of damage to voting machine there will not be harm to continuity of the election process. Results of election can be found out within minutes of completion of the election. Minimum manpower Utilization, hence mechanism is error free.
This document summarizes a student project on AI facial emotion detection. It includes sections on the problem setup and approach, different models tested including KNN, logistic regression, neural networks and CNNs, and a comparison of results. The most accurate model for facial emotion detection was a pre-trained VGG model using transfer learning, which achieved 68.2% accuracy. The project aims to help applications like assisting children with autism or improving online education. Future work could include creating a live camera feature to demonstrate the emotion detection model.
Identifying unconscious patients using face and fingerprint recognitionAsrarulhaq Maktedar
The presentation is about our project which helps to identify any unconscious person with help of face or fingerprint recognition, which is based on biometrics.
The presentation also explains the algorithm we used in our project
SourceAFIS used for Fingerprint Recognition
CNN ( Convolution Neural Network ) used for Face Recognition
The presentation also includes IEEE Reference Papers
There are multiple UI systems in Unity but uGUI is the latest and most commonly used. uGUI uses classes in the UnityEngine.UI namespace and components like Image, Text, and Button to build interfaces. Canvases are used to control where UI elements are positioned, either in screen space or world space. Cross resolution strategies like pixel size and screen size help UI scale appropriately on different screens. The event system allows communication between the UI and other game components through events. Exercises demonstrate creating a main menu with buttons, player input, and high score tracking using these uGUI systems.
4837410 automatic-facial-emotion-recognitionNgaire Taylor
This document summarizes an automatic facial emotion recognition system. It begins with an introduction to facial expression recognition and importance of understanding emotions. It then discusses related work on universal emotions and facial feature analysis. The system uses a facial tracker to extract features from tracked facial landmarks. Two classifiers, Naive Bayes and TAN, are used to classify emotions and results are visualized. The system includes a face detector for initialization and uses evaluation on recognition accuracy for different classifiers and dependency.
Calculator.ppt Andriod Application topicnoor ul ain
The document describes a calculator application created by a group of 6 students for Android devices. The calculator app features basic math functions like addition and multiplication as well as more complex functions like logarithms and working with matrices. It provides accurate results and graphs, works on both phones and tablets, and has no cost to users since it can be downloaded as an app rather than requiring a physical calculator.
mini project in c using data structure SWETALEENA2
This document describes a closet organizer project using data structures in C. The project aims to help users organize their clothes in their closet by allowing them to input details about each item like name, color, material and storage location. It also allows searching for a specific item's details and viewing the full closet contents. Users can add multiple clothing details through linked lists and remove items permanently by name. Sample outputs demonstrate adding details, searching for an item, viewing the full closet details, and deleting a item. The project aims to help users save time finding clothes and avoid buying duplicates.
This document summarizes a project to develop a simple calculator application using Java. It discusses the objectives of creating a basic calculator for arithmetic operations. It outlines what was learned technically about Java programming and Eclipse. It also describes the software requirements, intended end users as office workers and students, and ideas for future enhancements such as adding more scientific functions or interactive features using AI.
Question generation using Natural Language Processing by QuestGen.AIData Science Milan
Ramsri Goutham presented on generating multiple choice questions (MCQs) from text using natural language processing. He discussed using T5 transformers and sense2vec vectors to generate questions from news articles and generate wrong answer choices using WordNet and Sense2vec. Ramsri also shared an open source question generation library called Questgen and demonstrated generating MCQs from sample text about Elon Musk and cryptocurrencies in a Google Colab notebook.
In this tutorial, you will learn the basics of scripting in Unity by:
- Creating a new script component and adding it to a GameObject
- Exploring the default script structure and functions like Start and Update
- Adding a variable to the script and editing its value in the Inspector
- Using Debug.Log to output messages to the Console
- Changing a property of a GameObject by editing values in the script
This document presents an overview of a calculator application called "My Calculator". It discusses the features of the calculator, which include standard calculation functions, scientific calculations, unit conversion, GPA calculation, and solving mathematical problems. The document also provides information on the project status, implementation details using Java libraries and classes like Swing, JFrame and ActionListener. It was presented by three individuals and details the progress made on developing the calculator application.
This document summarizes face recognition techniques. It discusses three levels of facial details, from gross to micro features, and how they require different image resolutions. It also outlines the major components of a face recognition system: image acquisition, face detection, and face matching. Finally, it describes common image formats like 2D photos and 3D scans, and detection methods like Viola-Jones that use Haar-like features and AdaBoost training.
It's a new Windows based application for visually impaired person..!
This application will provides only, mail services for blinds and there's no voice duplications allowed during the user login.
This document outlines a project to design and develop a Sugar CRM bot using Artificial Intelligence Markup Language (AIML). The objective is to create a bot that can answer questions about Sugar CRM. It will be implemented as both a desktop and web application using programming languages like AIML, Python, and Adobe Flex. An automatic AIML generation tool will also be developed to ease the creation of AIML files. The source code for the project is available online for checkout and demonstration.
Emotion detection from text using data mining and text miningSakthi Dasans
Emotion detection from text using data mining and text mining
Based on research paper published by Faculty of Engineering, The University of Tokushima at IEEE 2007 we build an intelligent system under the title Emotelligence on Text to recognize human emotion from textual contents.
i.e. if you give an input string , our system would possibly able to say the emotion behind that textual content.
Complete power point presentation on SPEECH RECOGNITION TECHNOLOGY.
Very helpful for final year students for their seminar.
One can use this presentation as their final year seminar.
Speech Recognition is a very interesting topic for seminar.
This document presents a human emotion recognition system that uses facial expression analysis to identify emotions. It discusses how emotions are important to human life and interaction. The system first captures images of a human face and preprocesses the images to extract features. It then compares the facial features to examples in a database to recognize the emotion based on distances between features. The system can identify six basic emotions with up to 97% accuracy. Limitations and potential to incorporate fuzzy logic for improved classification are also discussed.
In the era of technology, the voting machine, which is present today, is highly unsecured. Being in the age of Computers we are compromising the security by opting for Electronic voting machine because in the present electronic voting machine is not intelligent that is it cannot determine the person came for the voting is eligible or not . That mean the whole control is kept in the hand of voting in charge officer. One more risk with the present voting machine is that anybody can increase the vote count, since the count is present in the machine itself.
In proposed machine that is “Global Wireless E-Voting” , The machine is made intelligent which can determine the eligibility of the voter by scanning the eye pattern and also the vote count is not kept into the same machine itself instead of it it is store in the remote server by converting it into radio waves. Here there is no chance of increasing the vote count of machine. Even in case of damage to voting machine there will not be harm to continuity of the election process. The machine provides high level of security, authentication, reliability, and corruption -free mechanism. By this we can get result within minute after a completion of voting. Minimum manpower Utilization, hence mechanism is error free.
Global Wireless E-Voting is an intelligent system which can determine the eligibility of the voter by scanning the eye pattern and also the vote count is not kept into the same machine itself instead of it is store in the remote server by converting it into radio waves.
.
The machine provides high level of security, authentication, reliability, and corruption -free mechanism. Here there is no chance of increasing the vote count of machine. Even in case of damage to voting machine there will not be harm to continuity of the election process. Results of election can be found out within minutes of completion of the election. Minimum manpower Utilization, hence mechanism is error free.
This document summarizes a student project on AI facial emotion detection. It includes sections on the problem setup and approach, different models tested including KNN, logistic regression, neural networks and CNNs, and a comparison of results. The most accurate model for facial emotion detection was a pre-trained VGG model using transfer learning, which achieved 68.2% accuracy. The project aims to help applications like assisting children with autism or improving online education. Future work could include creating a live camera feature to demonstrate the emotion detection model.
Identifying unconscious patients using face and fingerprint recognitionAsrarulhaq Maktedar
The presentation is about our project which helps to identify any unconscious person with help of face or fingerprint recognition, which is based on biometrics.
The presentation also explains the algorithm we used in our project
SourceAFIS used for Fingerprint Recognition
CNN ( Convolution Neural Network ) used for Face Recognition
The presentation also includes IEEE Reference Papers
There are multiple UI systems in Unity but uGUI is the latest and most commonly used. uGUI uses classes in the UnityEngine.UI namespace and components like Image, Text, and Button to build interfaces. Canvases are used to control where UI elements are positioned, either in screen space or world space. Cross resolution strategies like pixel size and screen size help UI scale appropriately on different screens. The event system allows communication between the UI and other game components through events. Exercises demonstrate creating a main menu with buttons, player input, and high score tracking using these uGUI systems.
4837410 automatic-facial-emotion-recognitionNgaire Taylor
This document summarizes an automatic facial emotion recognition system. It begins with an introduction to facial expression recognition and importance of understanding emotions. It then discusses related work on universal emotions and facial feature analysis. The system uses a facial tracker to extract features from tracked facial landmarks. Two classifiers, Naive Bayes and TAN, are used to classify emotions and results are visualized. The system includes a face detector for initialization and uses evaluation on recognition accuracy for different classifiers and dependency.
Calculator.ppt Andriod Application topicnoor ul ain
The document describes a calculator application created by a group of 6 students for Android devices. The calculator app features basic math functions like addition and multiplication as well as more complex functions like logarithms and working with matrices. It provides accurate results and graphs, works on both phones and tablets, and has no cost to users since it can be downloaded as an app rather than requiring a physical calculator.
mini project in c using data structure SWETALEENA2
This document describes a closet organizer project using data structures in C. The project aims to help users organize their clothes in their closet by allowing them to input details about each item like name, color, material and storage location. It also allows searching for a specific item's details and viewing the full closet contents. Users can add multiple clothing details through linked lists and remove items permanently by name. Sample outputs demonstrate adding details, searching for an item, viewing the full closet details, and deleting a item. The project aims to help users save time finding clothes and avoid buying duplicates.
This document summarizes a project to develop a simple calculator application using Java. It discusses the objectives of creating a basic calculator for arithmetic operations. It outlines what was learned technically about Java programming and Eclipse. It also describes the software requirements, intended end users as office workers and students, and ideas for future enhancements such as adding more scientific functions or interactive features using AI.
Question generation using Natural Language Processing by QuestGen.AIData Science Milan
Ramsri Goutham presented on generating multiple choice questions (MCQs) from text using natural language processing. He discussed using T5 transformers and sense2vec vectors to generate questions from news articles and generate wrong answer choices using WordNet and Sense2vec. Ramsri also shared an open source question generation library called Questgen and demonstrated generating MCQs from sample text about Elon Musk and cryptocurrencies in a Google Colab notebook.
This document summarizes emoji usage trends in 2022 based on data from the Facemoji Keyboard app. It finds that while new emoji were introduced in Unicode 14.0 in 2021, the most popular emoji of 2022 were older classics from Unicode 11.0 and before. It also observes creative uses of emoji through stories, symbols, and text art. The top emoji varied somewhat by country and app, but favorites like 😂, 🥺, and ❤️ remained widely used globally.
Emoji are standardized digital icons used in electronic communication to express ideas and emotions. They originated in Japan and can be used by businesses on social media to add personality, drive engagement through questions, and tell stories visually. When using emoji for weather communications, they can be implemented to draw attention, highlight details, and give forecasts a unique flair. Some cautions include using emoji sparingly and professionally.
Emojis are probably the most prolific pictorial language used today, but why? And what does it mean for conversation between businesses and customers? Is there a place for emojis in your dialogue with customers? In this talk, we’ll look at why we use emojis, some emoji history, and what we can learn from emojis about communication with others. I’ll share examples of emoji use from different brands and people, some with positive results and some exchanges that didn’t go so well.
ABOUT RACHEL PETERS
Once upon a time I was a high school English teacher. When I ran away screaming from that and into the arms of grad school, I discovered the world of UX, and I’ve been hooked ever since. Currently I’m the UX Lead for Launch Interactive, an agency in downtown Atlanta. You can learn more about Launch at http://www.launchjourney.com/.
Smile, Wink and Pray: Can Emojis Increase your Email Open Rate? (New Research)dlvr.it
Emojis Mostly Positive Affect on the Open-Rate of Your Marketing Emails. How including emojis in the subject line of your email can increase the open-rate of your marketing campaign.
View original post at: https://blog.dlvrit.com/2015/06/emojis/
This document discusses the use of emojis in social media. It defines emojis as standardized digital images used in electronic communication to express ideas and emotions. The document provides reasons why businesses should use emojis, such as to add personality, be playful, drive action and stand out. It also gives examples of how emojis can be used in weather reports and on platforms like Twitter and Facebook. Finally, it provides some cautions about using emojis sparingly and avoiding those that are not considered professional.
This document discusses the use of emojis in social media. It defines emojis as standardized digital images used in electronic communication to express ideas and emotions. The document provides reasons why businesses should use emojis, such as to add personality, be playful, drive action and stand out. It also gives examples of how emojis can be used in weather reports and on platforms like Twitter and Facebook. Finally, it provides some cautions about using emojis sparingly and avoiding those that are not considered professional.
The ability to automatically process and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. Since their introduction in the late 1990's, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. Processing emoji using traditional Natural Language Processing (NLP) techniques is a challenging task due to the pictorial nature of emoji and the fact that (the same) emoji may be used in different contexts and cultures to express different meanings. Their polysemous nature complicates tasks such as emoji similarity calculation and emoji sense disambiguation. Having access to machine-readable sense repositories that are specifically designed to capture emoji meaning can play a vital role in representing, contextually disambiguating, and converting pictorial forms of emoji into text, enabling NLP techniques to process this new medium of communication.
This dissertation presents EmojiNet, the largest machine-readable emoji sense inventory that links Unicode emoji representations to English meanings extracted from reliable online web sources. EmojiNet consists of: (i) 12,904 sense labels over 2,389 emoji linked to machine-readable sense definitions seen in BabelNet; (ii) context words associated with emoji senses based on word embedding models; and (iii) for some emoji, discrepancies in their presentation on different platforms. It further presents methods for emoji similarity evaluation and sense disambiguation uniquely enabled by EmojiNet. Emoji similarity methods are formed using word embedding models and are evaluated over a number of corpora. Those same embedding models are further used to carry out accuracy of emoji sense disambiguation. The EmojiNet framework, its RESTful web service, and benchmark datasets created as part of this dissertation are publicly released at http://emojinet.knoesis.org/.
Relevant publications: http://knoesis.org/Library?f%5Bsearch%5D=Sanjaya
Three of the top five most popular global emoji depict love. Laughter is also universally popular, with the crying laughing face ranking in the top three in every country. Half of Egypt's top 10 emoji are hearts. The skull emoji is only in the top 10 in the USA. New Year's Day saw the biggest spike in emoji usage over the past year. The most recently added emoji, folded hands, is the most popular globally.
Does your brand speak emojis on social media (1)Falcon.io
Flashback to the early 2000’s when emoticons were used on AIM Instant Messenger and MySpace. What feels prehistoric, was really just the evolution of emojis and the social media giants we have today. As marketers, it’s not enough anymore to just be where our customers are -- we need to speak their language. And if their language includes emojis, it’s important brands understand the benefits incorporating emojis into their social media strategy can have on their target audience.
In this webinar we are diving into:
- Why emojis belong in marketing
- How to incorporate emojis in marketing
- Emoji tips for social media
The ability to automatically process, derive meaning, and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. Yet the pictorial nature of emoji, the fact that (the same) emoji may be used in different contexts to express different meanings, and that emoji are used in different cultures over the world who interpret emoji differently, make it especially difficult to apply traditional Natural Language Processing (NLP) techniques to analyze them. This talk presents the creation of EmojiNet, the first machine-readable emoji sense repository that is designed by extracting emoji meanings from reliable online web sources and its applications for understanding emoji meaning in the social media text. It discusses how EmojiNet enables using NLP techniques to solve novel emoji research problems including emoji similarity and emoji sense disambiguation. A live demo of EmojiNet is available at http://emojinet.knoesis.org
This is the presentation to throw light upon the importance of Emojis in personal and in Digital Marketing, the various use of Emojis, Emojis expansion, etc
Note; The Presentation is also consistent with Videos which are not playable on Slideshare
IRJET- Dynamic Emotion Recognition and Emoji GenerationIRJET Journal
This document discusses a proposed system called Dynamic Emotion Recognition and Emoji Generation (DEmoji) that aims to improve upon existing static emoji generation systems. DEmoji will use facial tracking and expression recognition to dynamically generate emojis in real-time based on a person's facial expressions. It will also allow for generation of personalized emojis and sharing across different devices. The proposed system aims to provide a more innovative tool for digitally expressing emotions compared to current systems.
This document discusses robots, emojis, AI, and careers in AI. It explains how machine learning can be used to analyze emojis and determine sentiment based on facial features like concave eyes and mouth. Examples of AI applications from Google and Deepmind are mentioned. Different career roles related to machine learning, data science, and data engineering for an emoji analysis app are outlined.
Emojis are perceived by many as just a novel way to communicate, and most of us underestimate their value. Used right, emojis will make brands relatable, add context to your messaging, and appeal to your audience on a deeper level. And we all know that an emoji can be worth a thousand words. In this session, we’ll explore how using emojis will boost your social media engagement, the psychology behind emojis, whether it’s appropriate for your brand to use them in the first place and why it is essential for your brand to analyze emoji usage. Does your brand speak emoji yet?
The document discusses emoji and how they are used internationally to exchange ideas. It explains that emoji are part of Unicode so all devices can understand the same pictures. It notes that while Unicode provides code names for emoji in English, there is no source for official names in other languages. The document proposes creating an Emoji International Name Finder project to collect emoji names in different languages and share them online to help people understand emoji in languages other than English.
This document provides information on how to use the software Hotpotatoes to create educational games. Hotpotatoes allows you to make 6 types of games - JCloze for fill-in-the-blank, JMatch for matching, JQuiz for multiple choice quizzes, JCross for crosswords, JMix for rearranging sentences, and JMemory for memory games. The document explains how to download Hotpotatoes, create games of each type by adding questions, answers, and options to edit colors and text. It also provides examples of games created with Hotpotatoes and suggests making a page with links to all games.
This document describes an emoji widget module for Odoo. It allows users to add emoji widgets to character and text fields, allowing them to easily insert emojis. The module supports both the community and enterprise editions of Odoo and has been tested on the vanilla version. Key features include setting emoji widgets on fields, fetching emojis via symbols or text, viewing unicode representations, and typing codes to insert emojis. Configuration involves adding the appropriate widget to char or text fields.
I made my app more accessible and you won't believe what happened next...Sommer Panage
This talk discusses what it means go make an app accessible and why it matters. We delve into 10 simple and powerful ways to improve your product’s accessibility.
Understanding User Behavior with Google Analytics.pdfSEO Article Boost
Unlocking the full potential of Google Analytics is crucial for understanding and optimizing your website’s performance. This guide dives deep into the essential aspects of Google Analytics, from analyzing traffic sources to understanding user demographics and tracking user engagement.
Traffic Sources Analysis:
Discover where your website traffic originates. By examining the Acquisition section, you can identify whether visitors come from organic search, paid campaigns, direct visits, social media, or referral links. This knowledge helps in refining marketing strategies and optimizing resource allocation.
User Demographics Insights:
Gain a comprehensive view of your audience by exploring demographic data in the Audience section. Understand age, gender, and interests to tailor your marketing strategies effectively. Leverage this information to create personalized content and improve user engagement and conversion rates.
Tracking User Engagement:
Learn how to measure user interaction with your site through key metrics like bounce rate, average session duration, and pages per session. Enhance user experience by analyzing engagement metrics and implementing strategies to keep visitors engaged.
Conversion Rate Optimization:
Understand the importance of conversion rates and how to track them using Google Analytics. Set up Goals, analyze conversion funnels, segment your audience, and employ A/B testing to optimize your website for higher conversions. Utilize ecommerce tracking and multi-channel funnels for a detailed view of your sales performance and marketing channel contributions.
Custom Reports and Dashboards:
Create custom reports and dashboards to visualize and interpret data relevant to your business goals. Use advanced filters, segments, and visualization options to gain deeper insights. Incorporate custom dimensions and metrics for tailored data analysis. Integrate external data sources to enrich your analytics and make well-informed decisions.
This guide is designed to help you harness the power of Google Analytics for making data-driven decisions that enhance website performance and achieve your digital marketing objectives. Whether you are looking to improve SEO, refine your social media strategy, or boost conversion rates, understanding and utilizing Google Analytics is essential for your success.
Instagram has become one of the most popular social media platforms, allowing people to share photos, videos, and stories with their followers. Sometimes, though, you might want to view someone's story without them knowing.
Gen Z and the marketplaces - let's translate their needsLaura Szabó
The product workshop focused on exploring the requirements of Generation Z in relation to marketplace dynamics. We delved into their specific needs, examined the specifics in their shopping preferences, and analyzed their preferred methods for accessing information and making purchases within a marketplace. Through the study of real-life cases , we tried to gain valuable insights into enhancing the marketplace experience for Generation Z.
The workshop was held on the DMA Conference in Vienna June 2024.
Meet up Milano 14 _ Axpo Italia_ Migration from Mule3 (On-prem) to.pdfFlorence Consulting
Quattordicesimo Meetup di Milano, tenutosi a Milano il 23 Maggio 2024 dalle ore 17:00 alle ore 18:30 in presenza e da remoto.
Abbiamo parlato di come Axpo Italia S.p.A. ha ridotto il technical debt migrando le proprie APIs da Mule 3.9 a Mule 4.4 passando anche da on-premises a CloudHub 1.0.
Discover the benefits of outsourcing SEO to Indiadavidjhones387
"Discover the benefits of outsourcing SEO to India! From cost-effective services and expert professionals to round-the-clock work advantages, learn how your business can achieve digital success with Indian SEO solutions.
Ready to Unlock the Power of Blockchain!Toptal Tech
Imagine a world where data flows freely, yet remains secure. A world where trust is built into the fabric of every transaction. This is the promise of blockchain, a revolutionary technology poised to reshape our digital landscape.
Toptal Tech is at the forefront of this innovation, connecting you with the brightest minds in blockchain development. Together, we can unlock the potential of this transformative technology, building a future of transparency, security, and endless possibilities.
9. U+0030 = 0
U+0040 = A
U+0024 = $
U+1F602 = 😂
U+0000 to U+10FFFF 1,114,112
10.
11. emoji presentation
colorful and perhaps whimsical shapes, even animated
text presentation
black & white
U+2603 U+FE0F U+2603 U+FE0E
http://www.unicode.org/emoji/charts/emoji-variants.html
14. Diversity & Emoji Modifiers
Fitzpatrick Scale
a numerical classification schema for human skin color
15.
16. - When font doesn’t show the combined character, the user can still see that a skin tone was intended:
- When colorful emoji are not supported, fall back to a black and white stippled or hatched image
** To have an effect on an emoji, an emoji modifier must immediately follow that base emoji character.
** Emoji presentation selectors are neither needed nor recommended for emoji characters when they are followed by emoji
modifiers, and should not be used in newly generated emoji modifier sequences; the emoji modifier automatically implies the
emoji presentation style.
28. Things you want to know: Emoji domain & Punycode
- 2011: The World’s First Emoji
Domain!
- 2016: GoDaddy announced Emoji Domain Search Engine with
ASCII magic. All the registered and generated emoji-based
websites using GoDaddy's project are compatible with Google
search result.
Go to https://domainoji.com/ to register one!!
32. - Companies have updated their logos to striking emoji-like in
order to appeal more to today’s audiences.
- Nearly half of instagram text contains emojis.
- Product Hunt’s notifications are sent by emojis!
- Now you can search in Google using emojis !
33. Emoji in marketing
- Studies shows that emoji enabled ads have a 20 time
greater click-through than the industry average.
- Using emoji in email subject lines can increase your
open rates by over 20%
- Messages started by a business that contained an
emoji are four times more likely to elicit a response from
a consumer than those that don’t.
https://digiday.com/careers/year-emojis-5-charts/
39. Emoji Essentials
🚀 Rocket: Slack-style emoji everywhere on your Mac
🙏 Emoji.Life: Emojilytics for your Twitter timeline
🔎 Spotlight Emoji: Search and copy emoji inside Spotlight
☝️ EmojiOne: The best emoji Chrome extension around
Emoji Translators
💬 Emoji Translate: Turn your text into emoji automatically
📜 Bible Emoji Translator: Translate Bible verses into emoji-verses
️ Emojisaurus: Turn English phrases into emojigrams
📚 Emoji Dictionary: Quickly lookup any emoji meaning on Mac
💎 WhatMoji: A dictionary for all those confusing emojis
🌀 Emojilator: Translate English text to emoji
👾 Text to Emoji: A simple text to emoji converter Android app
👍 Decodemoji: Facebook bot that translates emojis to English
️ Botmoji: Emojipedia’s Twitter bot makes you an emoji master
Emoji for Developers
️ Emojicode: An emoji based programming language
️ Emoji CSS: Easily add Emoji’s to your website
💅 Designer Emojis: Vector emojis for designers
️ Pricemoji: An API for pricing products with emojis
✏️ Feedback Emoji: Capture user feedback with emojis
🐼 Gitmoji: An emoji guide for your GitHub commit messages
💻 Emoj: Find relevant emojis from text on the command-line
⚡️ Emoji Mart: A customizable emoji picker component for React
️ GH Emoji: A Github emoji parser you’ll love
😱 Emoji React: Add Emoji reactions to any webpage
💚 ❤❤❤.ws: Emoji website domain registration
The ultimate list of emoji products 😎
https://blog.producthunt.com/the-ultimate-list-of-emoji-products-
Emoji Utilities
️ Macmoji: Slack-style emoji for your mac! :smile:
🏠 Emoji Homepage: A fast way to find your emoji online
🚙 Emoji Engine: A search engine for emoji
🐙 Mosho.ws: Shorten URLs using emoji
🌐 Emojify: Shorten and create single-emoji URLs
🎩 Alfred Emoji Pack: Get :Slack: :style: emoji everywhere on Mac
😏 Browji for Chrome: Add emojis as you type on the web
Emoji Apps
📱 Moji: The App Store of emoji
📷 Fotomoji: Turn your photos and into an emoji explosion
👦 InstaEmoji: Replace your friend’s face with emoji
🔊 Audiots: Emoji’s you can hear! This is what emojis sound like!
🎓 Duolingo Emoji Language: The world’s first emoji language course
⌨ Swiftmoji: Emoji-predicting keyboard by Swiftkey
⬆️ Emoji Voting App: Addictive emoji voting on food, sports, and politics
😎 Memoji: Turn your face into an emoji using augmented reality
️ Emojify: Filters are boring. Add emoji to your photos instead
️ Secretmoji: Messages are scrambled into emojis until you unlock it
Emoji Fun
🎉 Emoji Party: An audio visual interactive emoji experience
️ Emoji Brush: Draw with emoji online
🎨 Emoji Mosaic: Upload and convert photos to an emoji portrait
🙈 Emojis & Earth Porn: Find the unmoving emoji amongst the beauty
🔑 Emoji Big Keys: The only big iOS keyboard with emojis
🔮 The Emojini 3000: Determines the best emojis for photos
🔀 Image2Emoji: Turn any image into a collage of emojis
✨ Emojigram: Turn words into emoji art
️ Picmoji: Super simple selfie to emoji art converter
👌 Emojify Everything: Replaces words on websites into emoji
45. Google Chrome
April Fool’s Day
Bonus Feature
On April Fools’ Day, we
gave users the chance
to translate the entire
mobile web into Emoji.
You could only access
this feature by
downloading or
updating the Chrome
app. To spread the
word of this very real
innovation we created
an April Fool’s Day
video. It foretold a
future where letters and
words are obsolete and
Emoji is the universal
language.
Pavan is not here?...😳 cave dwellers and cave arts.
The first emojis were developed in the late 1990s in Japan for use in the world's first mobile phone internet system.
Last year, MOMA acquired the original set of 176 emoji for its permanent collection. The collection was showed in the museum lobby from last year in December until March 12 this year, in a display that incorporates both 2D graphics and animations.
Emoji evoke art forms both ancient and modern, from hieroglyphics to manga. Their novelty is in how they’re deployed. As emoji are traded and spread and remixed by users, they become the medium for an internet-wide collaborative art project. Emoji may have started at DoCoMo and risen to the MoMA, but they belong to everyone and to no one.
https://www.nytimes.com/2016/10/27/arts/design/look-whos-smiley-now-moma-acquires-original-emoji.html
https://www.moma.org/calendar/exhibitions/3639
emojis became so popular across the world, lots of carriers / tech companies developed their own text encoding extensions, which were incompatible with one another.
So a proposal was made to the Unicode Consortium to expand the scope of symbols to encompass emoji. In 2007 the technical committee agreed to support the encoding of emoji in Unicode based on a set of principles developed by the subcommittee. Finally in 2010, emoji is formally adopted into Unicode standard.
a data file that maps every individual emoji symbol to a Unicode code point or sequence.
Certain characters can be followed by a special character called a variation selector to request a particular appearance
not all emojis have 2 different presentation sequences.
default, bright yellow skin color, racial diversity,
humans are supposed to be “generic”, shouldn’t only have one skin tone.
Some jokester asked that is yellow for the Simpsons? For people with jaundice? Not for Asians, surely?!
Fitzpatrick Scale, it is the most commonly used scheme to classify a person’s skin type by their response to sun exposure in terms of the degree of burning and tanning.
It was developed in 1975 by Thomas B. Fitzpatrick as a way to estimate the response of different types of skin to ultraviolet (UV) light.
Type I (scores 0–6) always burns, never tans (pale white; blond or red hair; blue eyes; freckles).
Type II (scores 7–13) usually burns, tans minimally (white; fair; blond or red hair; blue, green, or hazel eyes)
Type III (scores 14–20) sometimes mild burn, tans uniformly (cream white; fair with any hair or eye color)
Type IV (scores 21–27) burns minimally, always tans well (moderate brown)
Type V (scores 28–34) very rarely burns, tans very easily (dark brown)
Type VI (scores 35–36) Never burns, never tans (deeply pigmented dark brown to darkest brown)
only 5 different skin types in emoji modifiers. Unicode group the Fizpatrick scale type 1 and 2 into 1 type, (probably they don’t want too many whites ??? 😂), and define five modifiers to alter the neutral Emoji resulting in a variation having the desired skin tone.
degrades gracefully when you are dealing with an older system.
how emojis are rendered in different support levels.
Gas pump
acts like glue indicating that two code points should be represented as one single symbol when possible
Due to the way Emoji ZWJ Sequences are implemented, no prior approval is required before a vendor introduces a new one.
If a platform wants to get creative with many more ZWJ sequences, there is no technical limitation on this.
Google
new zero-width-joiner sequences to address the disparities in gender representation, and add more professions.
javascript uses UTF-16 as the string format. It means that only 2 to the power of 16 number of code points can fit into one single JavaScript code unit. This maps exactly to the BMP.
most of the emoji, which hex value is over ffff will need to do some conversation, it’s called finding a surrogate pair of the unicode.
Thanks to ES6, which introduce a new kind of escape sequence in strings, namely Unicode code point escapes. Additionally, it will define String.fromCodePoint and String#codePointAt, both of which accept code points rather than UTF-16-like code units.
So how to add new emojis? There is an organization called unicode consortium.
Only define emojis, not design them.
When adding new ones, the consortium would provide a code point, description / short name of it, and a black & white sketch for guidance, in order to form just the standardization of the symbols. For actually how to support emoji, as well as the specific design of the emoji characters, is up to software makers. Which is why that you would different versions of the smiley faces in different devices. https://unicode-table.com/
For an emoji domain to work, it must be converted into sth so-called "Punycode."
If anyone questioned the first emoji domain…
https://www.dnacademy.com/emoji-domains
Some pictographs are not emoji: WHITE SUN WITH RAYS ☼ U+263C xn--94h
Some characters are both pictographs and emoji: HOT SPRINGS U+2668 xn--j6h
Some emoji and not pictographs: MAN SWIMMING U+1F3CA [no IDN yet]
The world’s first emoji translator job was taken by a guy called Keith in 2017. In a company based in london called today translation.
Responsibilities include:
Client, stakeholder and internal emoji translation
Monthly reporting on emoji trends, developments, usage and areas of confusion and cultural differences
Cross-cultural research on differences in emoji usage/interpretation
Ad hoc consultancy and advice, as needed
https://www.todaytranslations.com/news/the-world-s-first-emoji-translator
study shows that a huge growth in the number of branded campaigns with emojis
http://cdn.emogi.com/docs/reports/2016_emoji_report.pdf
emojitracker, an experiment in real-time visualization of all emoji symbols used on twitter.
Emoji ransom generator!
Troy isn’t here?!!!
The ultimate list of emoji products 😎 !!!
Emoji data science !
Canvass, comments.
Instagram posted an article on Medium.
mobile app called dango which use deep learning behind to predict emoji based on natural text input. They also opened their sdk if you want to use.