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Full-Text Articles in Physical Sciences and Mathematics
Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar
Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar
Master's Projects
Neural Networks are now emerging in every industry. All the industries are trying their best to exploit the benefits of neural networks and deep learning to make predictions or simulate their ongoing process with the use of their generated data. The purpose of this report is to study the heating pattern of a silicon wafer and make predictions using various machine learning techniques. The heating of the silicon wafer involves various factors ranging from number of lamps, wafer properties and points taken in consideration to capture the heating temperature. This process involves dynamic inputs which facilitates the heating of the …
Classification Of Darknet Traffic By Application Type, Shruti Sharma
Classification Of Darknet Traffic By Application Type, Shruti Sharma
Master's Projects
The darknet is frequently exploited for illegal purposes and activities, which makes darknet traffic detection an important security topic. Previous research has focused on various classification techniques for darknet traffic using machine learning and deep learning. We extend previous work by considering the effectiveness of a wide range of machine learning and deep learning technique for the classification of darknet traffic by application type. We consider the CICDarknet2020 dataset, which has been used in many previous studies, thus enabling a direct comparison of our results to previous work. We find that XGBoost performs the best among the classifiers that we …
Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy
Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy
Master's Projects
Deep learning is one of the most advanced machine learning techniques, and its prominence has increased in recent years. Language processing, predictions in medical research and pattern recognition are few of the numerous fields in which it is widely utilized. Numerous modern medical applications benefit greatly from the implementation of machine learning (ML) models and the disruptive innovations in the entire modern health care system. It is extensively used for constructing accurate and robust statistical models from large volumes of medical data collected from a variety of sources in contemporary healthcare systems [1]. Due to privacy concerns that restrict access …
Enhancing Facial Emotion Recognition Using Image Processing With Cnn, Sourabh Deokar
Enhancing Facial Emotion Recognition Using Image Processing With Cnn, Sourabh Deokar
Master's Projects
Facial expression recognition (FER) has been a challenging task in computer vision for decades. With recent advancements in deep learning, convolutional neural networks (CNNs) have shown promising results in this field. However, the accuracy of FER using CNNs heavily relies on the quality of the input images and the size of the dataset. Moreover, even in pictures of the same person with the same expression, brightness, backdrop, and stance might change. These variations are emphasized when comparing pictures of individuals with varying ethnic backgrounds and facial features, which makes it challenging for deep-learning models to classify. In this paper, we …
A Study On Human Face Expressions Using Convolutional Neural Networks And Generative Adversarial Networks, Sriramm Muthyala Sudhakar
A Study On Human Face Expressions Using Convolutional Neural Networks And Generative Adversarial Networks, Sriramm Muthyala Sudhakar
Master's Projects
Human beings express themselves via words, signs, gestures, and facial emotions. Previous research using pre-trained convolutional models had been done by freezing the entire network and running the models without the use of any image processing techniques. In this research, we attempt to enhance the accuracy of many deep CNN architectures like ResNet and Senet, using a variety of different image processing techniques like Image Data Generator, Histogram Equalization, and UnSharpMask. We used FER 2013, which is a dataset containing multiple classes of images. While working on these models, we decided to take things to the next level, and we …
Task Classification During Visual Search Using Classic Machine Learning And Deep Learning, Devangi Vilas Chinchankar
Task Classification During Visual Search Using Classic Machine Learning And Deep Learning, Devangi Vilas Chinchankar
Master's Projects
In an average human life, the eyes not only passively scan visual scenes, but most times end up actively performing tasks including, but not limited to, searching, comparing, and counting. As a result of the advances in technology, we are observing a boost in the average screen time. Humans are now looking at an increasing number of screens and in turn images and videos. Understanding what scene a user is looking at and what type of visual task is being performed can be useful in developing intelligent user interfaces, and in virtual reality and augmented reality devices. In this research, …
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Master's Projects
Sentiment analysis is a method of understanding the user sentiment expressed in the form of text. Social media is the best place to capture the public's opinion regarding how they feel about current events. The Corona Virus Disease-2019 (COVID-19) is one of the worst pandemics we have experienced so far. An important observation is that this pandemic has not only affected the public's physical health but also took a toll on their mental health. Reddit is a social news discussion site where people discuss topics around current affairs in smaller groups called subreddits. The project's primary focus is to build …
Improving Facial Emotion Recognition With Image Processing And Deep Learning, Ksheeraj Sai Vepuri
Improving Facial Emotion Recognition With Image Processing And Deep Learning, Ksheeraj Sai Vepuri
Master's Projects
Humans often use facial expressions along with words in order to communicate effectively. There has been extensive study of how we can classify facial emotion with computer vision methodologies. These have had varying levels of success given challenges and the limitations of databases, such as static data or facial capture in non-real environments. Given this, we believe that new preprocessing techniques are required to improve the accuracy of facial detection models. In this paper, we propose a new yet simple method for facial expression recognition that enhances accuracy. We conducted our experiments on the FER-2013 dataset that contains static facial …
Visual And Lingual Emotion Recognition Using Deep Learning Techniques, Akshay Kajale
Visual And Lingual Emotion Recognition Using Deep Learning Techniques, Akshay Kajale
Master's Projects
Emotion recognition has been an integral part of many applications like video games, cognitive computing, and human computer interaction. Emotion can be recognized by many sources including speech, facial expressions, hand gestures and textual attributes. We have developed a prototype emotion recognition system using computer vision and natural language processing techniques. Our goal hybrid system uses mobile camera frames and features abstracted from speech named Mel Frequency Cepstral Coefficient (MFCC) to recognize the emotion of a person. To acknowledge the emotions based on facial expressions, we have developed a Convolutional Neural Network (CNN) model, which has an accuracy of 68%. …
Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen
Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen
Master's Projects
The spread of information about current events is a way for everybody in the world to learn and understand what is happening in the world. In essence, the news is an important and powerful tool that could be used by various groups of people to spread awareness and facts for the good of mankind. However, as information becomes easily and readily available for public access, the rise of deceptive news becomes an increasing concern. The reason is due to the fact that it will cause people to be misled and thus could affect the livelihood of themselves or others. The …
Ai Quantification Of Language Puzzle To Language Learning Generalization, Harita Shroff
Ai Quantification Of Language Puzzle To Language Learning Generalization, Harita Shroff
Master's Projects
Online language learning applications provide users multiple ways/games to learn a new language. Some of the ways include rearranging words in the foreign language sentences, filling in the blanks, providing flashcards, and many more. Primarily this research focused on quantifying the effectiveness of these games in learning a new language. Secondarily my goal for this project was to measure the effectiveness of exercises for transfer learning in machine translation. Currently, very little research has been done in this field except for the research conducted by the online platforms to provide assurance to their users [12]. Machine learning has been used …
Deep Learning Based Real Time Devanagari Character Recognition, Aseem Chhabra
Deep Learning Based Real Time Devanagari Character Recognition, Aseem Chhabra
Master's Projects
The revolutionization of the technology behind optical character recognition (OCR) has helped it to become one of those technologies that have found plenty of uses in the entire industrial space. Today, the OCR is available for several languages and have the capability to recognize the characters in real time, but there are some languages for which this technology has not developed much. All these advancements have been possible because of the introduction of concepts like artificial intelligence and deep learning. Deep Neural Networks have proven to be the best choice when it comes to a task involving recognition. There are …
Learning To Play The Trading Game, Neeraj Kulkarni
Learning To Play The Trading Game, Neeraj Kulkarni
Master's Projects
Can we train a stock trading bot that can take decisions in high-entropy envi- ronments like stock markets to generate profits based on some optimal policy? Can we further extend this learning for any general trading problem? Quantitative Al- gorithms are responsible for more than 75% of the stock trading around the world. Creating a stock market prediction model is comparatively easy. But creating a prof- itable prediction model is still considered as a challenging task in the field of machine learning and deep learning due to the unpredictability of the financial markets. Us- ing biologically inspired computing techniques of …
Detecting Cars In A Parking Lot Using Deep Learning, Samuel Ordonia
Detecting Cars In A Parking Lot Using Deep Learning, Samuel Ordonia
Master's Projects
Detection of cars in a parking lot with deep learning involves locating all objects of interest in a parking lot image and classifying the contents of all bounding boxes as cars. Because of the variety of shape, color, contrast, pose, and occlusion, a deep neural net was chosen to encompass all the significant features required by the detector to differentiate cars from not cars. In this project, car detection was accomplished with a convolutional neural net (CNN) based on the You Only Look Once (YOLO) model architectures. An application was built to train and validate a car detection CNN as …
Pose Estimation And Action Recognition In Sports And Fitness, Parth Vyas
Pose Estimation And Action Recognition In Sports And Fitness, Parth Vyas
Master's Projects
The emergence of large datasets and major improvements in Deep Learning has lead to many real-world applications. These applications have been focused on automotive markets, mobile markets, stock markets, and the healthcare market. Although Deep Learning has strong foundations across many areas, the few applications in Sports, Fitness, or even Injury Rehabilitation could benefit greatly from it. For example, if you are performing a workout and you need to evaluate your form, but do not have access or resources for an instructor to evaluate your form, it would be great to have an Artificial Intelligent agent provide real time feedback …
Deep Visual Recommendation System, Raksha Sunil
Deep Visual Recommendation System, Raksha Sunil
Master's Projects
Recommendation system is a filtering system that predicts ratings or preferences that a user might have. Recommendation system is an evolved form of our trivial information retrieval systems. In this paper, we present a technique to solve new item cold start problem. New item cold start problem occurs when a new item is added to a shopping website like Amazon.com. There is no metadata for this item, no ratings and no reviews because it’s a new item in the system. Absence of data results in no recommendation or bad recommendations. Our approach to solve new item cold start problem requires …