Training a latent variable based variational inference model on multimodal data in order to perform inference with all possible combinations of missing modalities.
A reproducibility test, ablation studies and extension of the seminal Generative Adversarial Networks paper
Identifying the highest number present in modified MNIST images containing multiple handwritten digits on random backgrounds using deep learning
We analyze different Machine Learning models to process Reddit data and develop a supervised classification model that can predict what community a certain comment came from.
Trained a biLSTM model using both word and character level embeddings for information retrieval from text OCR outputs of ID cards
We created a state of the art Optical Character Recognition Engine specifically for Indian ID cards using a pipeline for document layout detection, foreground extraction, text detection, recognition and postprocessing
Regression based deep learning models for automatically cropping document as foreground extraction(segmentation) task
Applying Machine Learning to March Madness College Basketball tournament for predicting tournament match results
Using traditional computer vision with deep learning algorithms for Anomalous activity detection from CCTV camera feed
Hindi and English digit recognition using MFCC features and five different neural networks and their performance evaluation under different conditions