Search Results for author: Jin Yuan

Found 15 papers, 6 papers with code

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.

Segmentation

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).

Segmentation

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).

Graph Attention Transformer Network for Multi-Label Image Classification

1 code implementation8 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

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

1 code implementation8 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 +1

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

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

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.

Segmentation

SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object Detection

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

To tackle this problem, this paper proposes a novel "Supervised Scale-aware Deformable Attention" (SSDA) for monocular 3D object detection.

Monocular 3D Object Detection Object +1

Epistemic Graph: A Plug-And-Play Module For Hybrid Representation Learning

no code implementations30 May 2023 Jin Yuan, Yang Zhang, Yangzhou Du, Zhongchao shi, Xin Geng, Jianping Fan, Yong Rui

In this paper, a novel Epistemic Graph Layer (EGLayer) is introduced to enable hybrid learning, enhancing the exchange of information between deep features and a structured knowledge graph.

Few-Shot Learning Knowledge Graphs +1

VPUFormer: Visual Prompt Unified Transformer for Interactive Image Segmentation

1 code implementation11 Jun 2023 Xu Zhang, Kailun Yang, Jiacheng Lin, Jin Yuan, Zhiyong Li, Shutao Li

Specifically, we design a Prompt-unified Encoder (PuE) by using Gaussian mapping to generate a unified one-dimensional vector for click, box, and scribble prompts, which well captures users' intentions as well as provides a denser representation of user prompts.

Image Segmentation Segmentation +1

Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation

1 code implementation2 Aug 2023 Guojin Zhong, Jin Yuan, Pan Wang, Kailun Yang, Weili Guan, Zhiyong Li

The recently rising markup-to-image generation poses greater challenges as compared to natural image generation, due to its low tolerance for errors as well as the complex sequence and context correlations between markup and rendered image.

Denoising Image Generation

S$^3$-MonoDETR: Supervised Shape&Scale-perceptive Deformable Transformer for Monocular 3D Object Detection

no code implementations2 Sep 2023 Xuan He, Kailun Yang, Junwei Zheng, Jin Yuan, Luis M. Bergasa, HUI ZHANG, Zhiyong Li

These methods typically use visual and depth representations to generate query points on objects, whose quality plays a decisive role in the detection accuracy.

Monocular 3D Object Detection object-detection

DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization

no code implementations5 Mar 2024 Feng Hou, Jin Yuan, Ying Yang, Yang Liu, Yang Zhang, Cheng Zhong, Zhongchao shi, Jianping Fan, Yong Rui, Zhiqiang He

With the recent advance of vision-language models (VLMs), viewed as natural source models, the cross-domain task changes to directly adapt the pre-trained source model to arbitrary target domains equipped with prior domain knowledge, and we name this task Adaptive Domain Generalization (ADG).

Domain Generalization

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