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OCR software, free and offline. 开源、免费的离线OCR软件。支持截屏/批量导入图片,PDF文档识别,排除水印/页眉页脚,扫描/生成二维码。内置多国语言库。
Dataset of medical images, captions, subfigure-subcaption annotations, and inline textual references
S2ORC: The Semantic Scholar Open Research Corpus: https://www.aclweb.org/anthology/2020.acl-main.447/
The official code to build up dataset PMC-OA
Transparent medical image AI via an image–text foundation model grounded in medical literature
Repo to reproduce the results for the paper "An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis". Accepted at ISICW @ ECCV 2022. Arxiv: https://arxiv.org/abs/2106.09229
PyTorch code and models for the DINOv2 self-supervised learning method.
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to ex…
Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation (CVPR 2023)
Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"
[CVPR 2023] Label-Free Liver Tumor Segmentation
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan…
[MICCAI 2019] [MEDIA 2020] Models Genesis
The official implementation for ICCV'23 paper "Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning"
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Universal LLM Deployment Engine with ML Compilation
[CVPR 2024 🔥] GeoChat, the first grounded Large Vision Language Model for Remote Sensing
AO2-DETR: Arbitrary-Oriented Object Detection Transformer
Reference implementations of MLPerf™ training benchmarks
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
[ECCV2024] API code for T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
Build deep learning applications in a new and easy way.
Library for Digital Pathology Image Processing