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Sign Language Recognition Using Deep Learning 4

Sign Language Recognition Using Deep Learning

引用

4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Nirmala, M. New Horizon College of Engineering Computer Science and Engineering Bangalore India

ISBN: (数字)9781665456487

ISBN: (纸本)9781665456487

the ability to converse with hearing and deaf persons has always been difficult for those who are tongue-Tied. In this paper, we can see different methods which are introduced to help them to communicate effectively. there are many human interpreters or assistant tools to help them communicate, but each person cannot afford that aid. the only mode of communication for them is sign language. therefore, the project's primary goal is to assist those individuals by providing a system that will recognize the signs, translate them into text, and enable them to lead a normal social life. Previously, a method including hand detection had been developed as a learning tool for novices in sign language. the system was developed using a method based on skin color modeling known as explicit skin-color space thresholding. the specified range of skin tones will distinguish between pixels, or the hand, and non-pixels, or the background. the photos were given as input to a model called the CNN a deep learning algorithm. We will be implementing this project using Keras to train the images. this document provides information on a variety of projects/research on sign language detection in the domains of machine learning, deep learning, and image depth data. this study considers a number of the numerous problems that must be overcome in order to overcome this problem, as well as the future scope. © 2022 IEEE.

关键词： Pixels

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Food Detection and Recognition Using Deep Learning - A Review 4

Food Detection and Recognition Using Deep Learning - A Revie...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Banerjee, Anushrie Bansal, Palak thomas, K.T. Christ University Department. of Data Science Lavasa Pune India

ISBN: (纸本)9781665474368

Studies show poor lifestyle choices and unhealthy eating patterns cause issues like obesity and other ongoing illnesses that raise the risk of heart attacks, such as hypertension, abnormal blood sugar levels, and diabetes. To improve this situation a lot of health apps have been built which use modern dietary monitoring systems that automatically evaluate dietary intake using machine learning and deep learning techniques rather. For these reasons indepth investigations on food detection, classification, and analysis have been conducted. Some of the top methods for automatic food recognition created have been discussed in this paper. We also propose an idea for detection of Indian food items using image classification. According to our findings of the papers we reviewed, convolutional neural networks (CNN) have been extensively been used in food detection as it has been giving better results compared to other models. We also observed that Vision transformers perform better in situations where the dataset is large and a hybrid model would give better accuracy. A review of potential applications for food image analysis, shortfalls in the area, and open issues concludes the paper. © 2022 IEEE.

关键词： Image classification

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Sentimental analysis on E-Learning videos using Hybrid Algorithm based on Naïve Bayes and SVM 4

Sentimental analysis on E-Learning videos using Hybrid Algor...

引用

4th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2022

作者： Rajesh, P. Akila, D. Department of Computer Science Chennai Pallavaram India Department of Information Technology Chennai Pallavaram India

ISBN: (纸本)9781665400732

E-learning has piqued the interest of companies, educational institutions, and people alike. E-learning systems are becoming increasingly prominent as an educational trend. It typically refers to educational attempts spread via the use of computers in an attempt to transmit information. Students can engage with other students and discuss questions about certain topics thanks to e-Learning platforms and similar technologies. Teachers, on the other hand, frequently remain outside of this process and are unaware of the learning issues that exist in their classes. Adopting a Sentiment Analysis approach for detecting the student mood throughout the learning process might be a solution for better learning method. In this paper, we used sentimental analysis on E-learning data. SVM and Naïve Bayes algorithms are fused to be used as a Hybrid algorithm for better accuracy. Performance analysis shows that state-of-art methods like Naïve Bayes and SVM algorithms give 90% and 94% respectively whereas our proposed hybrid method gives approximately 97% of accuracy. © 2022 IEEE.

关键词： Sentiment analysis

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Challenges of Digital Transformation in Education in India 4

Challenges of Digital Transformation in Education in India

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Shukla, Saurabh Jacob, Lija Christ Deemed to Be University Department of Data Science Pune India

ISBN: (纸本)9781665474368

Online learning has been present since the 1960s and has risen in popularity over time. World-class universities have been using online teaching-learning methodologies to fulfill the needs of students who reside far away from academic institutions for more than a decade. Many people predicted that online education would be the way of the future, but with the arrival of COVID-19, online education was imposed upon stakeholders far sooner and more suddenly than expected. When the COVID-19 pandemic broke out, educational institutions began to explore digital ways to keep students studying even when they couldn't be together in person as governments enacted legislation prohibiting large groups of people from gathering for any reason, including education. the future of such a transition looks promising. However, transitioning from one mode of education to another is not easy. Historically, when educators adopt new tools, learning still continues in the conventional manner. Based on the responses of 176 students, this paper studies the challenges of Digital transformation in the Education sector. the research is extremely beneficial in evaluating the scope of societal opposition to change. © 2022 IEEE.

关键词： Students

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Cardiovascular Disease Prediction Using KNN Algorithm 4

Cardiovascular Disease Prediction Using KNN Algorithm

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Choudhary, Shyam Sagar Singh Singh, Priyam Yadav, Dileep Kr. Galgotias University Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9781665474368

Innovation has made considerable progress in the course of the most recent couple of years, individuals presently use web as their base vehicle for recovering and trading data. Abundance isn't the main thing of our life which individuals search for nowadays. Well being was, is and it will be the genuine abundance for individual. Wellbeing shouldn't be stayed away from anytime in our life. Coronary illness is one of the most well-known factor for passing's in individual. Cardiovascular sickness is those which influences veins and causes heart infections. the past strategy of ascertaining the obscure measure of these illnesses ease in taking terms to bring down the higher gamble of *** well being office has colossal measure of information;the ML calculations helps in clearing the path for forecast and to control examination and medicine. In this examination, technique for eliminating missing information and properties characterization is utilized in per-handling for high precision and navigation. A portion of the calculations utilized for this thing like Decision Tree, KNN and Naive Bayes. Our point is to gather information mining techniques in Cardiovascular illness expectation, by utilizing basic boundary with the goal that it very well may be utilized in Machine 2 Machine remote observing. © 2022 IEEE.

关键词： Forecasting

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Multimodal Emotion Recognition Using Deep Learning Techniques 4

Multimodal Emotion Recognition Using Deep Learning Technique...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Jerald James, S. Jacob, Lija Christ University Department of Data Science Lavasa Pune India

ISBN: (纸本)9781665474368

Humans have the ability to perceive and depict a wide range of emotions. there are various models that can recognize seven primary emotions from facial expressions (joyful, gloomy, annoyed, dreadful, wonder, antipathy, and impartial). this can be accomplished by observing various activities such as facial muscle movements, speech, hand gestures, and so forth. Automatic emotion recognition is a significant issue that has been a hotly debated research topic in recent years. At the moment, several research people have taken a component in inheriting or extra multimodal for higher understanding. this paper indicates a method for emotion recognition that makes use of 3 modalities: facial images, audio indicators, and text detection from FER and CK+, RAVDESS, and Twitter tweets datasets, respectively. the CNN model achieved 66.67 percent on the FER-2013 dataset of labeled headshots while on the CK+ dataset, 98.4 percent accuracy was obtained. Finally, diverse fusion strategies had been approached, and each of those fusion techniques gave distinctive results. this project is a step towards the sense of interaction between human emotional aspects and the growing technology that is the future of development in today's world. © 2022 IEEE.

关键词： Emotion Recognition

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A Study of LSTM in Stock Price Prediction 4

A Study of LSTM in Stock Price Prediction

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Bairagi, Ishan Adhikari Daniel, A. Sharma, Anchal Galgotias University School of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9781665474368

Investing into stocks has become a trend in the new generation and everyone shows keen interest in putting their money and trying their luck into the stock game. But it requires deep analysis and thorough knowledge to get you through the risk and failures. there are multiple platforms which let you invest money into stocks nationally and internationally and with the boom in cryptocurrency, it has become evident that investments are an efficient way to earn and give us an upper hand over others as far as income parameters are concerned. this project aims to predict the price of the selected stock and give useful and near reliable insights so that investor can have an idea of how the stock may perform in the future. this can really help assess the performance of a stock and make calculated decisions. We intend to predict the stock using the LSTM neural network and then at a later stage provide the user with a dashboard using plotly dash for stock analysis. However stock prices are subject to market conditions and may change abruptly depending on multiple factors. thus the project aims to give supposed prices to the investor on an approximate basis. the future of this project can be made in a mobile based app which plugged in with previous performance of stock data will help users take advantage of the prediction at their hands. © 2022 IEEE.

关键词： Forecasting

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Application of machine learning algorithm for prediction of heart disease 4

Application of machine learning algorithm for prediction of ...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Upadhyay, Ankit Kumar Saleem, Sharzeel Anubhav, Adarsh Sagar, Shrddha Galgotias University Department of Computer Science and Engineering Greater Noida India Department of Electrical Electronics and Communications Galgotias University Greater Noida India

ISBN: (纸本)9781665474368

Healthcare is the one the domain in which every organization is working on it globally. It need to make it better and better via different researches and the innovations in this sector. Machine learning is the most used algorithm in every sector and organization. It not merely transforming the field of healthcare but also able to emulate the various human intelligence from the surrounding in order to solve various problems. Machine learning in health care sector has shown its various application in it. Disease prediction is one of the applications of it. this study helps to predict heart diseases with the help of its algorithm to determine the risk and treat the patient in the healthcare system. In this paper we have taken out the data from the kaggle and implemented it using the Jupiter notebook tool. the three algorithm we have implemented (naïve bayes, decision tree and random forest) out of which random forest is giving. Hence, with the help of the following algorithms it is possible for us to predict the heart disease with more accuracy. this research will able to predict various disease over its various symptoms more easily and accurately. © 2022 IEEE.

关键词： Forecasting

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An Integrated Approach for Suicidal Tendency Detection 4

An Integrated Approach for Suicidal Tendency Detection

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Baby, V. Sudheshna, Dama Sarvani, Desu Vesangi, Sahithi Regatte, Saketh Reddy Vnr Vignana Jyothi Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781665474368

Suicidal Tendency or the intention to kill oneself and end their life is a catastrophic situation which is mostly unknown by any person in the victim's life. In many studies it is evident that, victims tend to kill themselves either to end their pain, pressure or to have a relief that they are not going to live in this world anymore. Current suicidal tendency detection methods include numerous machine learning and deep learning approaches using clinical data or online social media, provide a solution to this existing problem. this paper aims to present a multi-modal approach that could help the victim's close ones to know if he/she is suffering from suicidal tendency. Providing a multi-faceted method that can detect this tendency and intimate the family, friends or the close ones beforehand can prove to be a boon for the invention. three different approaches like Facial Gesture Recognition, Voice Pattern Recognition and Text Pattern Recognition are imbibed in the Android Mobile Application and used as modules to determine suicidal intent in a complementary manner. Finally, the limitations and future scope are extrapolated to provide an overview for the future research. © 2022 IEEE.

关键词： Character recognition

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Key Features and Formation of Transactions in the Case of Using UTxO, EUTxO and Account Based data Storage Models 4

Key Features and Formation of Transactions in the Case of Us...

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4th international science and Technology conference "Modern Network Technologies", MoNeTec 2022

作者： Pomogalova, Albina V. Martyniuk, Anastasia A. Yesalov, Kirill E. Bonch-Bruevich Saint-Petersburg State University of Telecommunications Infocommunication Systems Department Saint Petersburg Russia Bonch-Bruevich Saint-Petersburg State University of Telecommunications Software Engineering and Computing Department Saint Petersburg Russia

ISBN: (数字)9781665472463

ISBN: (纸本)9781665472463

At the moment there are various logical concepts of constructing data storage and making transactions in blockchain networks. these concepts can be divided into account-based and (Extended) Unspent Transaction Output (E)UTxO. Account-based is a system with multiple accounts that can interact with each other through the creation and signing the transaction by a private key. While (E)UTxO is a model in which the values at the transaction outputs determine the current state of both a single smart contract and the entire blockchain network. To move from one state to another, transactions use the unspent outputs of previous transactions. the unspent outputs then become spent outputs: inputs for the new transaction also forming its unspent transaction outputs. these outputs can store both ADA and native tokens assigned to the public key. they can also store other information depending on the implementation of the script. the paper investigates the architectural features and differences of systems with two concepts of data storage construction, application features, as well as transaction construction models and the impact of models on network performance considered on the example of a practical case - development of an authorization module in the system. © 2022 IEEE.

关键词： Blockchain

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