To develop an autonomous vehicle using Arduino (Atmega-328p) & remote wireless supervisory control (using, XCTU & XBee or C#) with capability of ultrasonic obstacle detection & avoidance, self-park…

Developed a computer vision system for an autonomous vehicle capable of lane changing, avoiding vehicle collision by calculating relative vehicle speeds, etc. Used Hough Transform, Canny edge detec…

An end-to-end Self-driving car using CNN to map pixels from front-camera to steering angles on a simulator. This deep learning approach required minimum training data & the system learned to steer,…

Aim of this project is to use Computer Vision techniques of Deep Learning to correctly identify & map Brain Tumor for assistance in Robotic Surgery.

Foreseeing Survival Through ‘Fuzzy Intelligence’: A Cognitively-Inspired Incremental Learning Based de novo Model for Breast Cancer Prognosis by Multi-Omics Data Fusion

cAPTured: Neural Reflex Arc-Inspired Fuzzy Continual Learning for Capturing in Silico Aptamer-Target Protein Interactions

Research Project for Detection of COVID-19 from X-Ray using Deep Learning methods. Implemented convolutional neural network for classification of X-Ray Images into COVID & non-COVID cases.

We propose a new class of Computer-aided diagnosis models, i.e., Deep-Precognitive Diagnosis, wherein artificial agents are enabled to identify unknown diseases that have the potential to cause a p…

In this project, we use a Deep Recurrent Architecture, which uses CNN (VGG-16 Net) pretrained on ImageNet to extract 4096-Dimensional image feature Vector and an LSTM which generates a caption from…

This project aims to automatically detect surface defects in Hot-Rolled Steel Strips such as rolled-in scale, patches, crazing, pitted surface, inclusion and scratches. A CNN is trained on the NEU …