Deep learning and reinforced learning by Asheeh Kumar

Building deep Learning-based classifiers for the task of 'Emotion Classification' using Pytorch classifiers for Emotion. • Used CNN Lstm VGG16 Pre-trained model and Attention form Paper "Attention is all you need". • Multi-modal classifiers for disaster tweet classification using tweet text and image. • Experiments for Multi-lingual Multimodality for emotion classification and predicting Intensity score. • Evaluating all results using precision-recall and F1-score cosine-similarity and Pearsons correlation coefficient Artificially generate realistic labelled dataset | SWAAYATT ROBOTS 16th May 2018 - 10th July 2018 • Solved the problem of Night Vision using Multimodel Unsupervised Image to Image translation. • Implemented GANs and Autoencoder for style transfer to artificially generate realistic labelled datasets. • Generated Inverse Perspective Mapping software(C++) using USB cameras. Projects Road Accident analysis and Safety measures. | IIT Roorkee Feb-2019 March-2019 • Analyzing accident data and coming up with important factors in an accident by visualizing of road accident data from 2003-2016. • Building a Faster R-CNN model for Traffic sign Detection and classification using pytorch and Use this model to give warning on not following signs. Text to Narrate | IIT Roorkee Artificial Intelligence and Electronics Society Dec 2017 - Jan 2018 • Implemented bi-LSTM layer, Conditional Random Field (CRF) Named Entity Recognition. • Render related images to the user so as to visualize the story. • The final phase of the project was to combine the two sub-parts to provide a seamless experience for the end-user. • We have made the web-app with the help of Django.