CL-Detection2024-Baseline-UNet

Top solution of the MICCAI CLdetection2023 challenge

[MICCAI 2024] Cephalometric Landmark Detection across Ages with Prototypical Network

A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification

This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.

This in my Demo of Chen et al. "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks" ICML 2018

Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning adjustable weight coefficients.

Row-Column Scanned Neural Signed Distance Fields for Freehand 3D ultrasound Imaging Shape Reconstruction

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

LLM101n: Let's build a Storyteller

中文医学多模态大模型 Large Chinese Language-and-Vision Assistant for BioMedicine

[IEEE TMI 2024] Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification

Performer simple implementation using pytorch

Pytorch library for fast transformer implementations

SUPRA: Software Defined Ultrasound Processing for Real-Time Applications - An Open Source 2D and 3D Pipeline from Beamforming to B-Mode

Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation, NeurIPS 2021 Spotlight

Summary of related papers on visual attention. Related code will be released based on Jittor gradually.

Here is the implementation of Thyroid Ultrasound Image Segmentation

Code for paper "Lymphoma segmentation from 3D PET-CT images using a deep evidential network"

Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

Cardiac Segmentation - Trained networks, pre- and post-processing code

EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms

Simple pytorch implementation of FGSM and I-FGSM