Software Engineer at Pocketpills | COE DTU’22

github

Devashish Yadav  • Peerlist

Developed and designed a website that allows its users to view oxygen centers available on a map,rate, comment on them along with complete CRUD operations for Oxygen Centers .
Implemented complete user Authentication and Authorization
TechStack : Node.js, Express.js, MongoDB, Passport, JS, Mapbox API, EJS

Find My Oxygen

This project presents a fully automatic method for 3D segmentation of brain tissue on MRI scans using a modern deep learning approach and proposes 3D Dense-U-Net neural network architecture using densely connected layers. This project aims to distinguish gliomas which are the most difficult brain tumors to be detected with deep learning algorithms. For a skilled radiologist, analysis of multimodal MRI scans can take up to 20 minutes.
Model was trained using the Keras library and final accuracy came out to be 99.82%.

Brain MRI Tumor Segmentation

Faceable is a web app that uses the Clarifai API to locate a face in a picture. Using a React.js front-end and Node.js backend with Express.js as well as a PostgreSQL database to keep track of how many entries every user has made.

Faceable

Flask Web Application for Wired_Images-AI_Image_Captioning_Bot. With the help of this project, machine can generate its own captions related to the image and present it in an elegant manner. The model uses Flickr8k dataset for training data and uses LSTM for training and CNN for extracting the image features.