8 papers
LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +2
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc. In order to aid the training process, exi…
PLSM: A Parallelized Liquid State Machine for Unintentional Action Detection
Dipayan Das, Saumik Bhattacharya, Umapada Pal +1
Reservoir Computing (RC) offers a viable option to deploy AI algorithms on low-end embedded system platforms. Liquid State Machine (LSM) is a bio-inspired RC model that mimics the…
Multipath Graph Convolutional Neural Networks
Rangan Das, Bikram Boote, Saumik Bhattacharya +1
Graph convolution networks have recently garnered a lot of attention for representation learning on non-Euclidean feature spaces. Recent research has focused on stacking multiple l…
A Data-driven Understanding of COVID-19 Dynamics Using Sequential Genetic Algorithm Based Probabilistic Cellular Automata
Sayantari Ghosh, Saumik Bhattacharya
COVID-19 pandemic is severely impacting the lives of billions across the globe. Even after taking massive protective measures like nation-wide lockdowns, discontinuation of interna…
Computational model on COVID-19 Pandemic using Probabilistic Cellular Automata
Sayantari Ghosh, Saumik Bhattacharya
Coronavirus disease (COVID-19) which is caused by SARS-COV2 has become a pandemic. This disease is highly infectious and potentially fatal, causing a global public health concern.…
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +1
Compressive sensing (CS) is widely used to reduce the acquisition time of magnetic resonance imaging (MRI). Although state-of-the-art deep learning based methods have been able to…