Neelanjan Manna's repositories
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.
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.
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.
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.
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.
Neural-Style-Transfer
A neural style transfer algorithm which uses a CNN trained with a style-cost function. The style-cost function makes use of two images, the style-image and the content-image to produce an image which is the content-image re-drawn in the style of the style-image, referred to as the generated image. The generated-image thus resembles an artwork similar to the original content-image but bearing the style of the style-image.
chaos-charts
Repository to hold chaos experiments resource YAML bundles
chaos-operator
chaos engineering via kubernetes operator
chaos-runner
The bridge between chaos operator and chaos experiment! Lifecycle manager for chaos experiments
harness-chaos-demo
Simple Demo Block for Harness Chaos Engineering (standalone)
http-add-on
Add-on for KEDA to scale HTTP workloads
iptables-viz
A simple and scalable iptables visualisation tool which can integrate across Kubernetes and Linux.
litmus-docs
Repo for beta test of docusaurus-2 based litmus-documentation
Sukoon
We want to build open-source solutions and standards for using AI to solve mental health challenges. The goal is to apply DPI knowledge and practices that can help professionals deeply explore and understand the latest advancements in AI and how they can be applied to use-cases in mental health specific to India.
test-tools
A set of containerized applications, workload generators that will be consumed by openebs/e2e & openebs/litmus
To-Do-Single-Page-Application
A Single Page Application (SPA) made using AJAX, jQuery, Bootstrap, and JavaScript that serves as a daily to-do list.
v1-litmus-docs
Documentation for the Litmus Project