resnet-50 开源项目推荐（1,559 个）

ashishpatel26 /Tools-to-Design-or-Visualize-Architecture-of-Neural-Network

Tools to Design or Visualize Architecture of Neural Network

RubensZimbres /Repo-2017

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

pbaylies /stylegan-encoder

StyleGAN Encoder - converts real images to latent space

cvjena /cnn-models

ImageNet 为 Caffe 框架提供带有批处理规范化的预训练模型

peteryuX /retinaface-tf2

RetinaFace (Single-stage Dense Face Localisation in the Wild, 2019) implemented (ResNet50, MobileNetV2 trained on single GPU) in Tensorflow 2.0+. This is an unofficial implementation. With Colab.

alexisbcook /ResNetCAM-keras

Keras implementation of a ResNet-CAM model

AlexOlsen /DeepWeeds

用于深度学习的多类杂草物种图像数据集

rsomani95 /shot-type-classifier

Detecting cinema shot types using a ResNet-50

ElenaRyumina /EMO-AffectNetModel

Dynamic and static models for real-time facial emotion recognition

potterhsu /easy-faster-rcnn.pytorch

PyTorch 中快速 R-CNN（https://arxiv.org/pdf/1506.01497.pdf）的简单实现。

Alkoby /Bone-Fracture-Detection

利用深度学习进行骨折检测（Resnet50）——学位四年级的期末项目

bl0 /moco

Unofficial implementation with pytorch DistributedDataParallel for "MoCo: Momentum Contrast for Unsupervised Visual Representation Learning"

aksh-ai /neuralBlack

A Multi-Class Brain Tumor Classifier using Convolutional Neural Network with 99% Accuracy achieved by applying the method of Transfer Learning using Python and Pytorch Deep Learning Framework

potterhsu /easy-fpn.pytorch

PyTorch 中 FPN（https://arxiv.org/pdf/1612.03144.pdf）的简易实现。

avinabsaha /ReIQA

Official implementation for CVPR2023 Paper "Re-IQA : Unsupervised Learning for Image Quality Assessment in the Wild"

TripleCoenzyme /ResNet50-Unet

Segmentation for vertebra in MR images

CHENGY12 /DMML

code for ICCV19 paper "Deep Meta Metric Learning"

MichiganCOG /M-PACT

A one stop shop for all of your activity recognition needs.

rehg-lab /eye-contact-cnn

Deep neural network trained to detect eye contact from facial image

microsoft /art

Exploring the connections between artworks with deep "Visual Analogies"