Pak287's repositories
AttentionDeepMIL
Implementation of Attention-based Deep Multiple Instance Learning in PyTorch
Awesome-Vision-Attentions
Summary of related papers on visual attention. Related code will be released based on Jittor gradually.
Awesome-Visual-Transformer
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
BCL
A bayesian collaborative learning framework for whole-slide image classification
CLAM
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
CLIP_prefix_caption
Simple image captioning model
dataset
医学影像数据集列表
DCOD
Reconstruct in-line holograms with a single image.
dsmil-wsi
DSMIL: Multiple instance learning networks for tumor detection in Whole Slide Image
FusionDN
FusionDN: A Unified Densely Connected Network for Image Fusion
IRWSR
Python implementation of the Iterative Re-weighted Super Resolution scheme
Jittor-MLP
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLP, S2MLPv2, RaftMLP, HireMLP, ConvMLP, AS-MLP, SparseMLP, ConvMixer, SwinMLP, RepMLPNet, WaveMLP, MorphMLP, DynaMixer, MS-MLP, Sequencer2D in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!! trunc_normal_ is supported for Jittor!! MLP Paper is uploaded!
marugoto
Tools to build deep learning pipelines.
Multi-Frame-Super-Resolution
Non-sequential multi-frame super-resolution image generation
MultiFrameSuperResolution
A Multi Frame Super Resolution Tool based on Matlab
PMIL
Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from whole-slide pathological images
pytorch-grad-cam
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Examples for classification, object detection, segmentation, embedding networks and more. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
spring-2021
All code from my classes that is written from my spring 2021 semester.
SupER
Super-Resolution Erlangen (SupER): Benchmarking Super-Resolution Algorithms on Real Data
super_resolution
Super-resolution is a technique that constructs an high-resolution image from several observed low-resolution images.
SWARM
Swarm Learning for computational pathology
tmi2022
A graph-transformer for whole slide image classification
TransMIL
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
WENO
Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
WGDG_demo
Lensless imaging reconstruction code using Wirtinger gradient descent optimization