neelanjan00
Software Engineer II @harness | OSS Maintainer @cncf @litmuschaos | LFX Mentor @litmuschaos | React, Golang, Kubernetes, Cloud Foundry.
Repositories
Select a repository to view its commits, contributors, and more.Driver-Drowsiness-Detection
A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).
Parkinsons-Detection
An AI-based mobile application that is able to diagnose Parkinson's Disease using two independent tests that require only a pencil and a paper. Based on the 2017 research paper Distinguishing Different Stages of Parkinson's Disease Using Composite Index of Speed and Pen-Pressure of Sketching a Spiral by Zham et. al. The trained models were deployed using a Flask backend server, along with a Flutter based frontend mobile application frontend to interact with the REST API.
Image-Forgery-Detection
A deep convolutional neural network for the detection as well as localization of the area of manipulation in forged images, bearing forgeries of simple as well as complex nature. Further along, the trained model is interfaced with a web application for users to interact with the model in a simple and effective manner, and finally, we also develop a chatbot for further easing the process of interaction with the model and effectively tackling the problem of fake news forwards in popular internet messaging platforms such as WhatsApp.
Face-Recognition-Facenet-
An implementation of the Siamese Neural Network for facial recognition using one shot detection, that eliminates the requirement for the Neural Network to be trained each time a new image is added to the database. Trained using a Triplet Loss Function, it may even be used to perform the facial recognition with one training instance image.
Crop-AI
A diagnostic AI-enabled mobile app which is able to classify upto 38 different plant diseases ranging for 14 crops and vegetables. The application makes use of the VGG-Net CNN architecture for the purpose of multi-class classification of the images of infected plant leaves. The trained model was then deployed using a Flask backend server, along with a Flutter-based frontend mobile application to interact with the REST API.
ASL-Sign-Language-CV
A webcam-based object detection model that uses an artificial neural network to label the American Sign Language (ASL) hand sign alphabets. This deep learning model makes use of the Faster-RCNN model architecture to perform the object detection, which is implemented using the Tensorflow framework.
Sorting-Visualizer
A web application for visualising Bubble Sort, Insertion Sort, Selection Sort, Merge Sort and Quick Sort. The application is developed in next.js application developed along with react.js for server side rendering of react js application for improved SEO and support for hardware resources constrained devices. The codebase is written in Typescript instead of Javascript for better code understandability and maintainability.
Crop-AI-Frontend
A diagnostic AI-enabled mobile app which is able to classify upto 38 different plant diseases ranging for 14 crops and vegetables. The application makes use of the VGG-Net CNN architecture for the purpose of multi-class classification of the images of infected plant leaves. The trained model was then deployed using a Flask backend server, along with a Flutter based frontend mobile application to interact with the REST API.
gap-buffer
A Go implementation of the Gap Buffer data structure.
Blind-Vision
Assisting blind people with the help of image-captioning via a smartphone app. The application makes use of two neural networks, a CNN-based image feature extractor, and an LSTM based sentence generator. The user is able to submit images to the app, which are fed to the CNN feature extractor. The extracted features are then fed to the LSTM network to generate the sentence that describes the image, which is then read aloud to the user.
Grid-Path-Finder
A web app for finding and visualizing the path between a source position and a destination position in a grid using Graph algorithms such as BFS, DFS, Dijkstra, etc.
kubectl-count
kubectl-count plugin, counts Kubernetes resource instances.