A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

Implementation of popular deep learning networks with TensorRT network definition API

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

Keras model of NSFW detector

Classification models trained on ImageNet. Keras.

InceptionTime: Finding AlexNet for Time Series Classification

food image to recipe with deep convolutional neural networks.

Sign Language Gesture Recognition From Video Sequences Using RNN And CNN

Mobile AI Compute Engine Model Zoo

Core ML demo app with Unsplash API

Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier).

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

AI Papers

A Multiclass Weed Species Image Dataset for Deep Learning

Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models

COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can…

Deploying Keras models using TensorFlow Serving and Flask

BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagg…

This is the code repository for my Medium post "Understanding your Convolution network with Visualizations"

Supervised Classification of bird species 🐦 in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data [ICVGIPW'18]