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3dfasterrcnn_lungnoduledetector

ageestimateadience

Age and Gender Estimation Using Convolutional Neural Network

awesome-image-classification

A curated list of deep learning image classification papers and codes

classification_models

Classification models trained on ImageNet. Keras.

cvpr2019

cvpr2019／cvpr2018/cvpr2019 papers，极市团队整理

deep-learning-coursera

This repository contains the programming assignments for Deep Learning specialization courses by Andrew Ng. It deals with the following concepts. DNNs, Hyperparameter tuning, Regularization, Optimization, CNNs (LeNet5, AlexNet, VGG, ResNet, Inception Network), Transfer Learning (Neural Style Transfer), RNNs (LSTM, GRU) and Structuring Machine Learning Projects.

deep-learning-models

Keras code and weights files for popular deep learning models.

deep_learning_object_detection

A paper list of object detection using deep learning.

deeplearntoolbox

deeplung

WACV18 paper "DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification"

deepseed-3d-convnets-for-pulmonary-nodule-detection

DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder ConvNets for Pulmonary Nodule Detection

dsb2017

The solution of team 'grt123' in DSB2017

dsb2017-1

Code for 2nd place solution to the 2017 National Data Science Bowl

efficientdet

EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow

fpn_tensorflow

This is a tensorflow re-implementation of Feature Pyramid Networks for Object Detection.

gluon-cv

Gluon CV Toolkit

hw2_image_classification

利用TensorFlow（TF），本作业实现了一个基于full convolution stack、inception v2 module等模块的图片分类网络，纵向共包含10层包含参数的层，采用自己搭建的卷积层。对于dset1与dset2采用同样的网络结构，分别进行训练。最终在dset1验证集（约含900张图，下同）上的Top1分类准确率约为0.52，在dset2验证集上的Top1准确率约为0.63。在K80显卡的单核上，该模型的训练速度约为205张图每秒，最终所得模型的checkpoint约为45MB。

image_class

基于keras集成多种图像分类模型： VGG16、VGG19、InceptionV3、Xception、MobileNet、AlexNet、LeNet、ZF_Net、ResNet18、ResNet34、ResNet50、ResNet_101、ResNet_152、DenseNet

isbi2018-diagnostic-classification-of-lung-nodules-using-3d-neural-networks

Network Architecture for the ISBI_2018 paper : DIAGNOSTIC CLASSIFICATION OF LUNG NODULES USING 3D NEURAL NETWORKS

kaggle_ndsb2017

Kaggle datascience bowl 2017

luna16-lung-nodule-analysis-2016-challenge

LUNA16-Lung-Nodule-Analysis-2016-Challenge

mgicnn

Multi-scale Gradual Itegration Convolutional Neural Network for False Positive Reduction in Pulmonary Nodule Detection

mlnd

Udacity Machine Learning Nano Degree Courses

models

Models and examples built with TensorFlow

mutualnet

MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution (ECCV'20 Oral)

mytinystl

Achieve a tiny STL in C++11

oatpp

🌱Modern Web Framework for C++. High performance, simple API, cross platform, zero dependency.

printed-chinese-character-ocr

This is a Chinese Character ocr system based on Deep learning (VGG like CNN neural net work),this rep include trainning set generating,image preprocesing,NN model optimizing based on Keras high level NN framwork

pulmonary-nodule-detection-based-on-deep-learning

Using U-net, 3D CNN and cGAN to accomplish Pulmonary Nodule Detection. Also it's my undergraduate research program.

pulmonary-nodules-maskrcnn

Mask R-CNN for Pulmonary Nodules Diagnosis, using TensorFlow 天池医疗AI大赛：Mask R-CNN肺部结节智能检测（Segmentation + Classification）