convolutional-networks
There are 229 repositories under convolutional-networks topic.
milesial/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
thtrieu/darkflow
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
udacity/deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
quark0/darts
Differentiable architecture search for convolutional and recurrent networks
towhee-io/towhee
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
KupynOrest/DeblurGAN
Image Deblurring using Generative Adversarial Networks
TrustAGI-Lab/Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
666DZY666/micronet
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、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
wkentaro/pytorch-fcn
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
experiencor/keras-yolo2
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).
hurshd0/must-read-papers-for-ml
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
bentrevett/pytorch-image-classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
implus/PytorchInsight
a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results
infocusp/tf_cnnvis
CNN visualization tool in TensorFlow
ducha-aiki/caffenet-benchmark
Evaluation of the CNN design choices performance on ImageNet-2012.
cauchyturing/UCR_Time_Series_Classification_Deep_Learning_Baseline
Fully Convlutional Neural Networks for state-of-the-art time series classification
tobybreckon/fire-detection-cnn
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)
experiencor/self-driving-toy-car
A self driving toy car using end-to-end learning
FrancescoSaverioZuppichini/glasses
High-quality Neural Networks for Computer Vision 😎
ethanhe42/u-net
U-Net: Convolutional Networks for Biomedical Image Segmentation
buomsoo-kim/Easy-deep-learning-with-Keras
Keras tutorial for beginners (using TF backend)
AdicherlaVenkataSai/ml-workspace
Machine Learning (Beginners Hub), information(courses, books, cheat sheets, live sessions) related to machine learning, data science and python is available
skcript/tensorflow-resources
Curated Tensorflow code resources to help you get started with Deep Learning.
TNTLFreiburg/braindecode
Outdated, see new https://github.com/braindecode/braindecode
ai-med/squeeze_and_excitation
PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks
naszilla/naszilla
Naszilla is a Python library for neural architecture search (NAS)
AdalbertoCq/Deep-Learning-Specialization-Coursera
Deep Learning Specialization courses by Andrew Ng, deeplearning.ai
hoangcuong2011/Good-Papers
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
ducha-aiki/affnet
Code and weights for local feature affine shape estimation paper "Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability"
ImagingLab/Colorizing-with-GANs
Grayscale Image Colorization with Generative Adversarial Networks. https://arxiv.org/abs/1803.05400
hugochan/Eye-Tracker
Implemented and improved the iTracker model proposed in the paper "Eye Tracking for Everyone"
anuragranj/spynet
Spatial Pyramid Network for Optical Flow
uoip/SSD-variants
PyTorch implementation of several SSD based object detection algorithms.
wkentaro/fcn
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Issam28/Brain-tumor-segmentation
A deep learning based approach for brain tumor MRI segmentation.
JihongJu/keras-fcn
A playable implementation of Fully Convolutional Networks with Keras.