http://imatge-upc.github.io/vqa-2016-cvprw/
This thesis studies methods to solve Visual Question-Answering (VQA) tasks with a Deep Learning framework.As a preliminary step, we explore Long Short-Term Memory (LSTM) networks used in Natural Language Processing (NLP) to tackle Question-Answering (text based). We then modify the previous model to accept an image as an input in addition to the question. For this purpose, we explore the VGG-16 and K-CNN convolutional neural networks to extract visual features from the image. These are merged with the word embedding or with a sentence embedding of the question to predict the answer. This work was successfully submitted to the Visual Question Answering Challenge 2016, where it achieved a 53,62\% of accuracy in the test dataset. The developed software has followed the best programming practices and Python code style, providing a consistent baseline in Keras for different configurations.
presentation from my thesis defense on text summarization, discusses already existing state of art models along with efficiency of AMR or Abstract Meaning Representation for text summarization, we see how we can use AMRs with seq2seq models. We also discuss other techniques such as BPE or Byte Pair Encoding and its effectiveness for the task. Also we see how data augmentation with POS tags and AMRs effect the summarization with s2s learning.
This Presentation is on the topic of Driver drowsiness Detection .
In this presentation We will discuss the Techniques used to detect drowsiness and compare some techniques
In the end we conclude and provide some suggestions regarding future work.
Thanks
http://imatge-upc.github.io/vqa-2016-cvprw/
This thesis studies methods to solve Visual Question-Answering (VQA) tasks with a Deep Learning framework.As a preliminary step, we explore Long Short-Term Memory (LSTM) networks used in Natural Language Processing (NLP) to tackle Question-Answering (text based). We then modify the previous model to accept an image as an input in addition to the question. For this purpose, we explore the VGG-16 and K-CNN convolutional neural networks to extract visual features from the image. These are merged with the word embedding or with a sentence embedding of the question to predict the answer. This work was successfully submitted to the Visual Question Answering Challenge 2016, where it achieved a 53,62\% of accuracy in the test dataset. The developed software has followed the best programming practices and Python code style, providing a consistent baseline in Keras for different configurations.
presentation from my thesis defense on text summarization, discusses already existing state of art models along with efficiency of AMR or Abstract Meaning Representation for text summarization, we see how we can use AMRs with seq2seq models. We also discuss other techniques such as BPE or Byte Pair Encoding and its effectiveness for the task. Also we see how data augmentation with POS tags and AMRs effect the summarization with s2s learning.
This Presentation is on the topic of Driver drowsiness Detection .
In this presentation We will discuss the Techniques used to detect drowsiness and compare some techniques
In the end we conclude and provide some suggestions regarding future work.
Thanks
These are slides used for invited tutorial on "end-to-end text-to-speech synthesis", given at IEICE SP workshop held on 27th Jan 2019.
Part 1: Neural waveform modeling
Presenters: Xin Wang, Yusuke Yasuda (National Institute of Informatics, Japan)
https://imatge.upc.edu/web/publications/visual-question-answering-20
This bachelor's thesis explores di erent deep learning techniques to solve the Visual Question-Answering (VQA) task, whose aim is to answer questions about images. We study di erent Convolutional Neural Networks (CNN) to extract the visual representation from images: Kernelized-CNN (KCNN), VGG-16 and Residual Networks (ResNet). We also analyze the impact of using pre-computed word embeddings trained in large datasets (GloVe embeddings). Moreover, we examine di erent techniques of joining representations from di erent modalities. This work has been submitted to the second edition Visual Question Answering Challenge, and obtained a 43.48% of accuracy.
I mede this slide for the beginners of object detection.
Anchor box was really hard to understand for me, so I wrote about it as easy to understand as I can.
Let's overwhelmingly prosper!!
CAPTCHA and Convolutional neural network Bushra Jbawi
CAPTCHA is not a good choice for security those days
because we can break it by Convolutional neural network
Topics :
what is CAPTCHA ?
how can we break CAPTCHA ?
what is the architecture of CNN ?
In computer vision and image processing the concept of feature detection refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or connected regions. This lecture teaches you the basics of feature detection.
https://www.udemy.com/learn-computer-vision-machine-vision-and-image-processing-in-labview/?couponCode=SlideShare
recognizer for a language, Deterministic finite automata, Non-deterministic finite automata, conversion of NFA to DFA, Regular Expression to NFA, Thomsons Construction
arithmetic and adaptive arithmetic codingAyush Gupta
Data compression techniques in Multimedia and data transmission in digital computers. You can solve the given question on board the solution is on YT. If you search there you'll find it in a few minutes. Hope it'll help you.......
Improving Neural Abstractive Text Summarization with Prior KnowledgeGaetano Rossiello, PhD
Abstractive text summarization is a complex task whose goal is to generate a concise version of a text without necessarily reusing the sentences from the original source, but still preserving the meaning and the key contents. In this position paper we address this issue by modeling the problem as a sequence to sequence learning and exploiting Recurrent Neural Networks (RNN). Moreover, we discuss the idea of combining RNNs and probabilistic models in a unified way in order to incorporate prior knowledge, such as linguistic features. We believe that this approach can obtain better performance than the state-of-the-art models for generating well-formed summaries.
These are slides used for invited tutorial on "end-to-end text-to-speech synthesis", given at IEICE SP workshop held on 27th Jan 2019.
Part 1: Neural waveform modeling
Presenters: Xin Wang, Yusuke Yasuda (National Institute of Informatics, Japan)
https://imatge.upc.edu/web/publications/visual-question-answering-20
This bachelor's thesis explores di erent deep learning techniques to solve the Visual Question-Answering (VQA) task, whose aim is to answer questions about images. We study di erent Convolutional Neural Networks (CNN) to extract the visual representation from images: Kernelized-CNN (KCNN), VGG-16 and Residual Networks (ResNet). We also analyze the impact of using pre-computed word embeddings trained in large datasets (GloVe embeddings). Moreover, we examine di erent techniques of joining representations from di erent modalities. This work has been submitted to the second edition Visual Question Answering Challenge, and obtained a 43.48% of accuracy.
I mede this slide for the beginners of object detection.
Anchor box was really hard to understand for me, so I wrote about it as easy to understand as I can.
Let's overwhelmingly prosper!!
CAPTCHA and Convolutional neural network Bushra Jbawi
CAPTCHA is not a good choice for security those days
because we can break it by Convolutional neural network
Topics :
what is CAPTCHA ?
how can we break CAPTCHA ?
what is the architecture of CNN ?
In computer vision and image processing the concept of feature detection refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or connected regions. This lecture teaches you the basics of feature detection.
https://www.udemy.com/learn-computer-vision-machine-vision-and-image-processing-in-labview/?couponCode=SlideShare
recognizer for a language, Deterministic finite automata, Non-deterministic finite automata, conversion of NFA to DFA, Regular Expression to NFA, Thomsons Construction
arithmetic and adaptive arithmetic codingAyush Gupta
Data compression techniques in Multimedia and data transmission in digital computers. You can solve the given question on board the solution is on YT. If you search there you'll find it in a few minutes. Hope it'll help you.......
Improving Neural Abstractive Text Summarization with Prior KnowledgeGaetano Rossiello, PhD
Abstractive text summarization is a complex task whose goal is to generate a concise version of a text without necessarily reusing the sentences from the original source, but still preserving the meaning and the key contents. In this position paper we address this issue by modeling the problem as a sequence to sequence learning and exploiting Recurrent Neural Networks (RNN). Moreover, we discuss the idea of combining RNNs and probabilistic models in a unified way in order to incorporate prior knowledge, such as linguistic features. We believe that this approach can obtain better performance than the state-of-the-art models for generating well-formed summaries.
(Paper Seminar detailed version) BART: Denoising Sequence-to-Sequence Pre-tra...hyunyoung Lee
(Detailed version) Paper seminar in NLP lab on "BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension"(2021.03.04)
(Paper Seminar short version) BART: Denoising Sequence-to-Sequence Pre-traini...hyunyoung Lee
(Short version) Paper seminar in NLP lab on "BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension"(2021.03.04)
Paper seminar of Neural Machine Translation Inspired Binary Code Similarity Comparison beyond Function Pairs in 2019 fall semester in Advanced Information Security class(2019.10.24).
Word embedding method of sms messages for spam message filteringhyunyoung Lee
This is presentation of 2019 the 6th IEEE International Conference on Big data and Smart Computing(ASC(the 3rd International Workshop on Affective and Sentimental Computing) of IEEE BigComp 2019), Feb. 2019. (2019. 02. 27)
Natural language processing open seminar For Tensorflow usagehyunyoung Lee
This is presentation for Natural Language Processing open seminar in Kookmin University.
The open seminar reference : https://cafe.naver.com/nlpk
My presentation about how to use tensorflow for NLP open seminar for newbies for tensorflow.
large-scale and language-oblivious code authorship identificationhyunyoung Lee
Paper seminar of Large-Scale and Language-Oblivious Code Authorship Identification in 2018 2 semester in Advanced Topics in Computer Science class(2018.11.06).
This is presentation to inform how to use NLTK(Natural Language Processing Toolkit) with NLTK book's simple examples in Information Retrieval and Data mining class as TA(2017.11.28).
This is presentation about what skip-gram and CBOW is in seminar of Natural Language Processing Labs.
- how to make vector of words using skip-gram & CBOW.
E-commerce Application Development Company.pdfHornet Dynamics
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
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AI Fusion Buddy Review: Key Features
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Looking for a reliable mobile app development company in Noida? Look no further than Drona Infotech. We specialize in creating customized apps for your business needs.
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Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
AI Genie Review: World’s First Open AI WordPress Website CreatorGoogle
AI Genie Review: World’s First Open AI WordPress Website Creator
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https://sumonreview.com/ai-genie-review
AI Genie Review: Key Features
✅Creates Limitless Real-Time Unique Content, auto-publishing Posts, Pages & Images directly from Chat GPT & Open AI on WordPress in any Niche
✅First & Only Google Bard Approved Software That Publishes 100% Original, SEO Friendly Content using Open AI
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✅Choose the temperature of the content and control its randomness.
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✅Never Worry About Paying Huge Money Monthly To Top Content Creation Platforms
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See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
#AIGenieApp #AIGenieBonus #AIGenieBonuses #AIGenieDemo #AIGenieDownload #AIGenieLegit #AIGenieLiveDemo #AIGenieOTO #AIGeniePreview #AIGenieReview #AIGenieReviewandBonus #AIGenieScamorLegit #AIGenieSoftware #AIGenieUpgrades #AIGenieUpsells #HowDoesAlGenie #HowtoBuyAIGenie #HowtoMakeMoneywithAIGenie #MakeMoneyOnline #MakeMoneywithAIGenie
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
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See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
