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 coefficientArtificially 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.ProjectsRoad 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.--- Send in a voice message: https://podcasters.spotify.com/pod/show/david-nishimoto/message