PyTorch implementation of the U-Net for image semantic segmentation with high quality images

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

Differentiable architecture search for convolutional and recurrent networks

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Image Deblurring using Generative Adversarial Networks

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、reg…

Paper Lists for Graph Neural Networks

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results

CNN visualization tool in TensorFlow

Evaluation of the CNN design choices performance on ImageNet-2012.

Fully Convlutional Neural Networks for state-of-the-art time series classification

real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)

A self driving toy car using end-to-end learning

High-quality Neural Networks for Computer Vision 😎

U-Net: Convolutional Networks for Biomedical Image Segmentation