Yash Indulkar

About

I completed my undergraduate degree from Thakur College of Science & Commerce (University of Mumbai) in Information Technology. Currently I'm pursuing my Post-Graduate degree in Information Technology from Thakur College of Science & Commerce, along with working as an IT Associate in ICICI Prudential Life Insurance Company.
My research areas are Convolutional Neural Network, Bayesian Deep Learning, Long Short Term Memory Networks etc on the Theoretical Side and Protein Sequence Analysis, Natural Language Processing, Object Detection & Tracking, Pattern Recognition etc on the Application Side.
More broadly, I am interested in Deep Learning and Computer Vision with an approach to optimize and increase the Accuracy & Speed.
The communities I follow are ICCTAW, ICIMMI, ICOSEC, ICICV, MVAI, MICCAI, MIDL and WACV.

Employment

• ICICI Prudentials Associate
  2020 - Present

Education

• University of Mumbai
  2017 - 2020

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• Alleviation of COVID by means of Social Distancing & Face Mask Detection Using YOLO V4
  2021 International Conference on Communication information and Computing Technology (ICCICT) 2021 DOI: 10.1109/iccict50803.2021.9510168
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• Comparative Study of Machine Learning Algorithms for Twitter Sentiment Analysis
  2021 International Conference on Emerging Smart Computing and Informatics (ESCI) 2021 DOI: 10.1109/esci50559.2021.9396925
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• PUBG Winner Ranking Prediction using R Interface ‘h2o’ Scalable Machine Learning Platform
  2021 International Conference on Emerging Smart Computing and Informatics (ESCI) 2021 DOI: 10.1109/esci50559.2021.9396823
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• Time Series Analysis of Cryptocurrencies Using Deep Learning & Fbprophet
  2021 International Conference on Emerging Smart Computing and Informatics (ESCI) 2021 DOI: 10.1109/esci50559.2021.9397004
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• Effects of Uber and Ola on SVM and Naïve Bayes
  Lecture Notes in Networks and Systems 2021 DOI: 10.1007/978-981-15-9689-6_53
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• Sentiment Analysis of Uber & Ola using Deep Learning
  2020 International Conference on Smart Electronics and Communication (ICOSEC) 2020 DOI: 10.1109/icosec49089.2020.9215429
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