[TIP-2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"

Iterate.ai has open-sourced a powerful Weapons Detection AI software. The AI was trained on about 100 live guns, plus 20,000 videos of robberies and threats involving weapons. Our engineers taught the AI to detect guns, knives, kevlar vests, and robbery masks.

Extended Mask R-CNN for RGB-D object instance segmentation based on Matterport's implementation. Segmentation accuracy improved by up to 31% using the additional depth input channel.

Self-Supervised Feature Learning by Learning to Spot Artifacts. In CVPR, 2018.

A project for ticketing automated challan for overspeeding vehicles on a decentralized network, and generating dynamic traffic signal timings based on traffic.

This repository provide script to do OCR using some basic Deep Learning approach

Automatic Building Footprint Segmentation: U-Net Production-Level API

Project: 2D Feature Tracking || Udacity: Sensor Fusion Engineer Nanodegree

This is a list of Computer Science free courses and resources available on Github and internet.

Notes and key takeaways of the Self-Driving Cars Perception applied Deep Learning Free Course from freeCodeCamp.org

Building A Virtual AI Keyboard Using CV On Pycham IDE

Extract text from handwritten infomation on bank checks images

This is shape detection program . It can detect shapes like triangle ,square, rectangle , circle and other shapes as well .

Caffe2-vision help engineer to build vision CNN for training and product, including dataset maker and favorite models

My projects that involve and use machine learning, data science and deep learning techniques with solve or observe a specfic use case

Convex Polygon Detection

Crop the object from the video and get it's tracking live over the web-cam.

matlab script for creating box around face.

Diagnose the presence of skin cancer in a person using CNN and as well explain what led the CNN to arrive at the decision. Visual explanations are made utilizing the Gradient-weighted Class Activation Mapping (Grad-CAM), the gradients flowing into the final convolutional layer to produce a coarse localization map highlighting the important regio…

Refer Readme.md