Detected Kinship with 85.5% accuracy on Families in Wild dataset between a pair of images using Siamese Networks , with features getting transfer learned from VGG16 network with adam optimizer and binary cross entropy loss function.
Aspect Based Sentiment Analysis(under Prof. Aruna Malapati)
Split sentences into multi-level clusters based on their multiple subjects in sentence using Optics Clustering
Extracted aspects and associated words relevant in the sentence using attention based modeling of sentence
Determined Sentiment polarity of the entire sentence both and also of concerned aspect term by using Long Short term memory network
Predicted the correct results of india’s lok sabha election by doing attention based sentiment analysis of tweets
Created a scoring mechanism associated with different types of twitter activities with retweet getting less weightage compared to original tweets and people with more followers getting more weightage compared to others.
Generated base vital signs data based on the “Novel coronavirus infection during the 2019–2020 epidemic” in Sichuan Province, China. Analyzed vitals signs data using deep learning in keras for suspected COVID patients
Presented at BARDA Industry Day Lightning Talks by US Health Department
Enhanced educational videos with natural language processing and computer vision by providing text summarization, POS tagging & NER for general knowledge and completed the fully functional prototype in form of a website within just 36 hours at Hack Harvard
Anterior Chamber Depth and Corneal Thickness at Srujana Innovation Center
Project: Constructed a miniature prototype that helps in early detection of Glaucoma Disease by using the Slit width image of an eye
Worked on Image segmentation and Image analysis techniques using Python, OpenCV, Raspi3, matplotlib to calculate Anterior Chamber Depth and Corneal thickness.
Awarded the best team award in 5th Engineering the eye Hackathon organized by MIT MEDIA LAB and Srujana Innovation
Market Basket Analysis
Market Basket Analysis and Mining Association Rules Project: Proposed a model that analyzes customer behavior iterating through different range of values for support and confidence • Used Apriori Principle and FP Tree for candidate pruning and rule generation • Formulated a model that gives insight about customers shopping patterns and also suggest the viable offers. • Tools: C++, FpTrees, Apriori Principle, Association Rule Mining