This document describes a bird identification system using deep learning. The system was developed to classify bird species from images using a convolutional neural network (CNN) with ResNet-18 transfer learning. The researchers used the Caltech-UCSD Birds 200 dataset to train and test the model on Google Colab using PyTorch. Transfer learning improved the model's accuracy, achieving a test accuracy of 78.8% at classifying bird species from images.
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of
agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the
diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various
kinds of interactions between humans and insects. There have been several attempts to create a method to
perform insect identification accurately. Great knowledge and experience on entomology are required for
accurateinsect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. This paper provides a review of the past literature in vision-based insect recognition
and classifications. Over the past decades, automatic insect recognition and classification has been given
extra attention especially in term of crop pest and disease control. This paper details advances in insect
recognition, discussing representative works from different types of method and classifiers
algorithm.Among the method used in the previous research includes color histogram, edge detection and
feature extraction (SIFT vector). We provides discussion on the state-of-the-art and provides perspective
on future research direction in insect recognition and classification problem.
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various kinds of interactions between humans and insects. There have been several attempts to create a method to perform insect identification accurately. Great knowledge and experience on entomology are required for accurate insect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. This paper provides a review of the past literature in vision-based insect recognition and classifications. Over the past decades, automatic insect recognition and classification has been given extra attention especially in term of crop pest and disease control. This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of
agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the
diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various
kinds of interactions between humans and insects. There have been several attempts to create a method to
perform insect identification accurately. Great knowledge and experience on entomology are required for
accurateinsect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. This paper provides a review of the past literature in vision-based insect recognition
and classifications. Over the past decades, automatic insect recognition and classification has been given
extra attention especially in term of crop pest and disease control. This paper details advances in insect
recognition, discussing representative works from different types of method and classifiers
algorithm.Among the method used in the previous research includes color histogram, edge detection and
feature extraction (SIFT vector). We provides discussion on the state-of-the-art and provides perspective
on future research direction in insect recognition and classification problem.
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various kinds of interactions between humans and insects. There have been several attempts to create a method to perform insect identification accurately. Great knowledge and experience on entomology are required for accurate insect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. This paper provides a review of the past literature in vision-based insect recognition and classifications. Over the past decades, automatic insect recognition and classification has been given extra attention especially in term of crop pest and disease control. This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.
AI_BIRDER: USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING TO CREATE A MOBILE...mlaij
Birds are everywhere around us and are easy to spot. However, for many beginner birders, identifying the
birds is a hard task [8]. There are many apps that help the birder to identify the birds, but they are often
too complicated and require good internet to give a result. A better app is needed so that birders can
identify birds while not depending on internet connection.
My app, AI_Bider, is mainly built in android studio using flutter and firebase, and the AI engine is coded
with TensorFlow and trained with images from the internet [9]. To test my AI engine, I made six different
prototypes, each having a different number of times that the code will train from the dataset of pictures. I
then selected 5 birds that are in my dataset and found 5 pictures on the internet for each of them, which I
then uploaded to the app. My app will then give me 3 bird species that most closely resemble the image, as
well as the app’s confidence in its choices, which are listed as percentages [6]. I recorded the percentages
of accuracy for each picture. After taking the average percentage of all the models, I selected the most
successful model, which had an average percent of accuracy of 79%.
Ai_Birder: Using Artificial Intelligence and Deep Learning to Create a Mobile...mlaij
Birds are everywhere around us and are easy to spot. However, for many beginner birders, identifying the birds is a hard task [8]. There are many apps that help the birder to identify the birds, but they are often too complicated and require good internet to give a result. A better app is needed so that birders can identify birds while not depending on internet connection.
My app, AI_Bider, is mainly built in android studio using flutter and firebase, and the AI engine is coded with TensorFlow and trained with images from the internet [9]. To test my AI engine, I made six different prototypes, each having a different number of times that the code will train from the dataset of pictures. I then selected 5 birds that are in my dataset and found 5 pictures on the internet for each of them, which I then uploaded to the app. My app will then give me 3 bird species that most closely resemble the image, as well as the app’s confidence in its choices, which are listed as percentages [6]. I recorded the percentages of accuracy for each picture. After taking the average percentage of all the models, I selected the most successful model, which had an average percent of accuracy of 79%.
Transform Domain Based Iris Recognition using EMD and FFTIOSRJVSP
Iris is one of the physiological trait which is used to identify the individuals. In this paper Transform Domain Based Iris Recognition using EMD and FFT is proposed. Circular Hough Transform is used in the Preprocessing stage to extract circular part of eye. The circular iris part is converted into rectangular rubber sheet model in Region of Interest (ROI).Empirical Mode Functions (EMF)’s are obtained by applying Empirical Mode Decomposition (EMD) on the Iris. FFT is also applied on ROI to extract the features. These features are added arithmetically to obtain final features. The features of the database are compared with test iris using Euclidian Distance(ED) to compute performance parameters. It is observed that the values of CRR and EER are better in the case of propsed algorithm compared to existing algorithms.
Vision based entomology how to effectively exploit color and shape featurescseij
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of
agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the
diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various kinds
of interactions between humans and insects. There have been several attempts to create a method to
perform insect identification accurately. Great knowledge and experience on entomology are required for
accurate insect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. We propose an automatic insect identification framework that can identify
grasshoppers and butterflies from colored images. Two classes of insects are chosen for a proof-ofconcept.
Classification is achieved by manipulating insects’ color and their shape feature since each class
of sample case has different color and distinctive body shapes. The proposed insect identification process
starts by extracting features from samples and splitting them into two training sets. One training
emphasizes on computing RGB features while the other one is normalized to estimate the area of binary
color that signifies the shape of the insect. SVM classifier is used to train the data obtained. Final decision
of the classifier combines the result of these two features to determine which class an unknown instance
belong to. The preliminary results demonstrate the efficacy and efficiency of our two-step automatic insect
identification approach and motivate us to extend this framework to identify a variety of other species of
insects.
AI_BIRDER: USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING TO CREATE A MOBILE...mlaij
Birds are everywhere around us and are easy to spot. However, for many beginner birders, identifying the
birds is a hard task [8]. There are many apps that help the birder to identify the birds, but they are often
too complicated and require good internet to give a result. A better app is needed so that birders can
identify birds while not depending on internet connection.
My app, AI_Bider, is mainly built in android studio using flutter and firebase, and the AI engine is coded
with TensorFlow and trained with images from the internet [9]. To test my AI engine, I made six different
prototypes, each having a different number of times that the code will train from the dataset of pictures. I
then selected 5 birds that are in my dataset and found 5 pictures on the internet for each of them, which I
then uploaded to the app. My app will then give me 3 bird species that most closely resemble the image, as
well as the app’s confidence in its choices, which are listed as percentages [6]. I recorded the percentages
of accuracy for each picture. After taking the average percentage of all the models, I selected the most
successful model, which had an average percent of accuracy of 79%.
Ai_Birder: Using Artificial Intelligence and Deep Learning to Create a Mobile...mlaij
Birds are everywhere around us and are easy to spot. However, for many beginner birders, identifying the birds is a hard task [8]. There are many apps that help the birder to identify the birds, but they are often too complicated and require good internet to give a result. A better app is needed so that birders can identify birds while not depending on internet connection.
My app, AI_Bider, is mainly built in android studio using flutter and firebase, and the AI engine is coded with TensorFlow and trained with images from the internet [9]. To test my AI engine, I made six different prototypes, each having a different number of times that the code will train from the dataset of pictures. I then selected 5 birds that are in my dataset and found 5 pictures on the internet for each of them, which I then uploaded to the app. My app will then give me 3 bird species that most closely resemble the image, as well as the app’s confidence in its choices, which are listed as percentages [6]. I recorded the percentages of accuracy for each picture. After taking the average percentage of all the models, I selected the most successful model, which had an average percent of accuracy of 79%.
Transform Domain Based Iris Recognition using EMD and FFTIOSRJVSP
Iris is one of the physiological trait which is used to identify the individuals. In this paper Transform Domain Based Iris Recognition using EMD and FFT is proposed. Circular Hough Transform is used in the Preprocessing stage to extract circular part of eye. The circular iris part is converted into rectangular rubber sheet model in Region of Interest (ROI).Empirical Mode Functions (EMF)’s are obtained by applying Empirical Mode Decomposition (EMD) on the Iris. FFT is also applied on ROI to extract the features. These features are added arithmetically to obtain final features. The features of the database are compared with test iris using Euclidian Distance(ED) to compute performance parameters. It is observed that the values of CRR and EER are better in the case of propsed algorithm compared to existing algorithms.
Vision based entomology how to effectively exploit color and shape featurescseij
Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of
agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the
diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account
for more than two thirds of these known species. Since 400 million years ago, there have been various kinds
of interactions between humans and insects. There have been several attempts to create a method to
perform insect identification accurately. Great knowledge and experience on entomology are required for
accurate insect identification. Automation of insect identification is required because there is a shortage of
skilled entomologists. We propose an automatic insect identification framework that can identify
grasshoppers and butterflies from colored images. Two classes of insects are chosen for a proof-ofconcept.
Classification is achieved by manipulating insects’ color and their shape feature since each class
of sample case has different color and distinctive body shapes. The proposed insect identification process
starts by extracting features from samples and splitting them into two training sets. One training
emphasizes on computing RGB features while the other one is normalized to estimate the area of binary
color that signifies the shape of the insect. SVM classifier is used to train the data obtained. Final decision
of the classifier combines the result of these two features to determine which class an unknown instance
belong to. The preliminary results demonstrate the efficacy and efficiency of our two-step automatic insect
identification approach and motivate us to extend this framework to identify a variety of other species of
insects.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.