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TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Unsupervised Learning for Image Registration
Segmentation deep learning ALgorithm based on MONai toolbox: single and multi-label segmentation software developed by QIMP team-Vienna.
医学影像数据集列表 『An Index for Medical Imaging Datasets』
3D ResNets for Action Recognition (CVPR 2018)
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
scikit-learn: machine learning in Python
Deep Learning for End-to-End Kidney Cancer Diagnosis on Multi-Phase Abdominal Computed Tomography
A Web Player for 360 Video on the Oculus
Image augmentation for machine learning experiments.
Source code for SpatialExtractor-TemporalEncoder-Integration-Classifier (STIC) model
including unet,unet++,attention-unet,r2unet,cenet,segnet ,fcn.
3D-Unet: patched based Pytorch implementation for medical images segmentation
Paper and implementation of UNet-related model.
[MICCAI 2021 Challenge] The official baseline model for MICCAI Challenge: Fast and Low GPU memory Abdominal oRgan sEgmentation (FLARE21)
JunMa11 / myvi
Forked from Image-Py/myviShow 3D segmentation results with the lightweight myvi.
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
2nd place solution to the Ultra-high Resolution EM Images Segmentation Challenge hosted by BAAI and PKU
Semantic Segmentation Architectures Implemented in PyTorch
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Urbanization detection using computer vision algorithms to reduce the reliance on the data of government surveys, which will speed up the policy making process.
主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。
深度学习入门教程, 优秀文章, Deep Learning Tutorial