baichi1212345
Follow
Stars
Training foundational medical imaging models using multi-task learning.
A transformer-based weakly supervised computational pathology method for clinical-grade diagnosis and molecular state revelation of gliomas
CellViT: Vision Transformers for Precise Cell Segmentation and Classification
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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…
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
[CVPR 2024] Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
Codebase for "A Foundation Model for Cell Segmentation"
Open deep learning compiler stack for cpu, gpu and specialized accelerators
A framework for high-performance medical image processing, neural network inference and visualization
Multi-lingual medical image registration library
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
StarDist - Object Detection with Star-convex Shapes
RT-Thread is an open source IoT real-time operating system (RTOS).
Deepspeed、LLM、Medical_Dialogue、医疗大模型、预训练、微调
An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
📝A simple and elegant markdown editor, available for Linux, macOS and Windows.
Smooth Loss Functions for Deep Top-k Classification
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
The official gpt4free repository | various collection of powerful language models
Generate duplex/single consensus reads to reduce sequencing noises and remove duplications
Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)
Tools for working with genomic and high throughput sequencing data.