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

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…

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

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

CNN visualization tool in TensorFlow

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)

U-Net: Convolutional Networks for Biomedical Image Segmentation

Curated Tensorflow code resources to help you get started with Deep Learning.

Outdated, see new https://github.com/braindecode/braindecode

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

Naszilla is a Python library for neural architecture search (NAS)

Code and weights for local feature affine shape estimation paper "Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability"

Grayscale Image Colorization with Generative Adversarial Networks. https://arxiv.org/abs/1803.05400

PyTorch implementation of several SSD based object detection algorithms.

Implemented and improved the iTracker model proposed in the paper "Eye Tracking for Everyone"