6928 Open source projects that are alternatives of or similar to Tianchi Medical Lungtumordetect

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

High level network definitions with pre-trained weights in TensorFlow

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

记录每一个常用的深度模型结构的特点（图和代码）

用python做计算机视觉，人工智能，机器学习，深度学习等

A collection of deep learning models (PyTorch implemtation)

PyTorch implementation of DeepDream algorithm

unet for image segmentation

Various CNN models for CIFAR10 with Chainer

This implements training of popular model architectures, such as AlexNet, ResNet and VGG on the ImageNet dataset(Now we supported alexnet, vgg, resnet, squeezenet, densenet)

This is a code repository for pytorch c++ (or libtorch) tutorial.

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

《深度学习与计算机视觉》配套代码

Classification with PyTorch.

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

food image to recipe with deep convolutional neural networks.

Speech commands recognition with PyTorch

Classification models trained on ImageNet. Keras.

AI Papers

Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)

Tensorflow implementation : U-net and FCN with global convolution

猫狗大战

Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.

Develop production ready deep learning code, deploy it and scale it

Deep fusion project of deeply-fused nets, and the study on the connection to ensembling

Kaggle airbus ship detection challenge 21st solution

A PyTorch implementation of PointRend: Image Segmentation as Rendering

fastai V2 implementation of Timeseries classification papers.

a generalist algorithm for cellular segmentation

Create mxnet finetuner (retrain) for mac/linux ,no need install docker and supports CPU, GPU(eGpu/cudnn).support the inception,resnet ,squeeznet,mobilenet...

A list of popular deep learning models related to classification, segmentation and detection problems

Urban building extraction in Daejeon region using Modified Residual U-Net (Modified ResUnet) and applying post-processing.

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Brainy is a virtual MRI analyzer. Just upload the MRI scan file and get 3 different classes of tumors detected and segmented. In Beta.

基于Tensorflow2开发的优秀扩展包及项目

A tool for running deep learning algorithms for semantic segmentation with satellite imagery

Smart India Hackathon 2019 project given by the Department of Atomic Energy

Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network

Classification and Segmentation with Mask-RCNN of Skin Cancer using ISIC dataset

SimpleAICV:pytorch training example on ImageNet(ILSVRC2012)/COCO2017/VOC2007+2012 datasets.Include ResNet/DarkNet/RetinaNet/FCOS/CenterNet/TTFNet/YOLOv3/YOLOv4/YOLOv5/YOLOX.

OpenMMLab Model Compression Toolbox and Benchmark.

This is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".

An open-source semi-automated processing chain for urban OBIA classification.

我的笔记和Demo，包含分类，检测、分割、知识蒸馏。

Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device" @ CAD&Graphics2019

Gluon to PyTorch deep neural network model converter

A Python toolbox for computer vision research and project

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

ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics

Computer vision library for wildfire detection

No description or website provided.

practice on CIFAR10 with Keras

Depth estimation from RGB images using fully convolutional neural networks.

Resurces for MRI images processing and deep learning in 3D

RM Operation can equivalently convert ResNet to VGG, which is better for pruning; and can help RepVGG perform better when the depth is large.

TensorFlow implementation of Faster RCNN for Object Detection

Inflated 3D ConvNets for video understanding