Stars
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Pytorch🍊🍉 is delicious, just eat it! 😋😋
Segment Anything in Medical Images
标注自己的数据集，训练、评估、测试、部署自己的人工智能算法
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
3D U-Net model for volumetric semantic segmentation written in pytorch
该资源为作者在CSDN的撰写Python图像处理文章的支撑，主要是Python实现图像处理、图像识别、图像分类等算法代码实现，希望该资源对您有所帮助，一起加油。
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics
Code for "Deep Snake for Real-Time Instance Segmentation" CVPR 2020 oral
TensorFlow 最佳学习资源大全（含课程、书籍、博客、公开课等内容）
Official implementation of SAM-Med2D
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
[CVPR 2024] Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
[MICCAI 2019 Young Scientist Award] [MEDIA 2020 Best Paper Award] Models Genesis
A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.
DeepSurv is a deep learning approach to survival analysis.
Segment Anything for Microscopy
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
[NeurIPS 2021] [T-PAMI] Global Filter Networks for Image Classification
[Pattern Recognition 25] CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks
Examples of using deep learning in Bioinformatics
天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet
Code for CVPR'19 paper Linkage-based Face Clustering via GCN