Search Results for author: Jin Yuan

Found 9 papers, 2 papers with code

SSD-MonoDTR: Supervised Scale-constrained Deformable Transformer for Monocular 3D Object Detection

1 code implementation12 May 2023 Xuan He, Fan Yang, Jiacheng Lin, Haolong Fu, Jin Yuan, Kailun Yang, Zhiyong Li

Specifically, SSDA presets several masks with different scales and utilizes depth and visual features to predict the local feature for each query.

Monocular 3D Object Detection object-detection

OMSN and FAROS: OCTA Microstructure Segmentation Network and Fully Annotated Retinal OCTA Segmentation Dataset

no code implementations26 Dec 2022 Peng Xiao, Xiaodong Hu, Ke Ma, Gengyuan Wang, Ziqing Feng, Yuancong Huang, Jin Yuan

The lack of efficient segmentation methods and fully-labeled datasets limits the comprehensive assessment of optical coherence tomography angiography (OCTA) microstructures like retinal vessel network (RVN) and foveal avascular zone (FAZ), which are of great value in ophthalmic and systematic diseases evaluation.

Learning to Learn Domain-invariant Parameters for Domain Generalization

no code implementations4 Nov 2022 Feng Hou, Yao Zhang, Yang Liu, Jin Yuan, Cheng Zhong, Yang Zhang, Zhongchao shi, Jianping Fan, Zhiqiang He

Due to domain shift, deep neural networks (DNNs) usually fail to generalize well on unknown test data in practice.

Domain Generalization

Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma

no code implementations29 Apr 2022 Liangrui Pan, Hetian Wang, Lian Wang, Boya Ji, Mingting Liu, Mitchai Chongcheawchamnan, Jin Yuan, Shaoliang Peng

The study proposes a typical transformer image classification framework by integrating noise reduction convolutional autoencoder and feature cross fusion learning (NRCA-FCFL) to classify osteosarcoma histological images.

Image Classification

Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation

no code implementations8 Apr 2022 Jin Yuan, Feng Hou, Yangzhou Du, Zhongchao shi, Xin Geng, Jianping Fan, Yong Rui

Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA) is very attractive for real world applications.

Domain Adaptation Self-Supervised Learning

Graph Attention Transformer Network for Multi-Label Image Classification

no code implementations8 Mar 2022 Jin Yuan, Shikai Chen, Yao Zhang, Zhongchao shi, Xin Geng, Jianping Fan, Yong Rui

Subsequently, we design the graph attention transformer layer to transfer this adjacency matrix to adapt to the current domain.

Classification Graph Attention +2

A Survey of Visual Transformers

1 code implementation11 Nov 2021 Yang Liu, Yao Zhang, Yixin Wang, Feng Hou, Jin Yuan, Jiang Tian, Yang Zhang, Zhongchao shi, Jianping Fan, Zhiqiang He

Transformer, an attention-based encoder-decoder model, has already revolutionized the field of natural language processing (NLP).

An automated and multi-parametric algorithm for objective analysis of meibography images

no code implementations29 Oct 2020 Peng Xiao, Zhongzhou Luo, Yuqing Deng, Gengyuan Wang, Jin Yuan

Meibography is a non-contact imaging technique used by ophthalmologists to assist in the evaluation and diagnosis of meibomian gland dysfunction (MGD).

Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images

no code implementations22 Aug 2019 Jiexiang Wang, Cheng Bian, Meng Li, Xin Yang, Kai Ma, Wenao Ma, Jin Yuan, Xinghao Ding, Yefeng Zheng

Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases.

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