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.

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