Image recognition and classification using Convolutional Neural Networks with TensorFlow

Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.

What would you say if I told you there is a app on the market that tell you if you have a jackfruit or not a jackfruit.

Introduces the utilization of MMdnn(a model converter) and provide a simple GUI for inference task of image classification.

Self Driving Car ND Project 12 - Semantic Segmentation

TinyYoloV2 imagenet 1K results.

PyTorch implementation of DiracDeltaNet from paper Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs

Fashion Image CNN Classifier using Keras

Tensorflow Faster R-CNN for Windows and Python 3.5

A deep learning based application which is entitled to help the visually impaired people. The application automatically generates the textual description of what's happening in front of the camera and conveys it to person through audio. It is capable of recognising faces and tell user whether a known person is standing in front of him or not.

A cannabis-trained DeepDream.

short training script for ViT, Swin-T, CvT, MsViT and Dino

A Web App made for image identification using Keras, ResNet-50 and Django

VoVNet V2 implementation and checkpoints

Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet

Unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s"

Unofficial PyTorch Implementation of "Augmenting Convolutional networks with attention-based aggregation"

Classification models trained on ImageNet. Keras.

Artificial Intelligence in Assistive Technology. Using AI and Machine Learning we can redefine what vision means for visually impaired or blind.

Library for image classification