Search Results for author: Zhiqiang He

Found 29 papers, 13 papers with code

Unleashing the Power of Graph Learning through LLM-based Autonomous Agents

no code implementations8 Sep 2023 Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao

With these agents, those components are processed by decomposing and completing step by step, thereby generating a solution for the given data automatically, regardless of the learning task on node or graph.

AutoML Graph Learning

Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach

no code implementations20 Nov 2022 Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao

Despite the success, we observe two aspects that can be further improved: (a) enhancing the ego feature information extraction from node itself which is more reliable in extracting the intra-class information; (b) designing node-wise GNNs can better adapt to the nodes with different homophily ratios.

Graph Representation Learning Neural Architecture Search +1

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

SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency

1 code implementation CVPR 2023 Yang Liu, Yao Zhang, Yixin Wang, Yang Zhang, Jiang Tian, Zhongchao shi, Jianping Fan, Zhiqiang He

To bridge the gap between the reference points of salient queries and Transformer detectors, we propose SAlient Point-based DETR (SAP-DETR) by treating object detection as a transformation from salient points to instance objects.

object-detection Object Detection

Deep Learning-based Occluded Person Re-identification: A Survey

no code implementations29 Jul 2022 Yunjie Peng, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang, Zhiqiang He

After that, we summarize and compare the performance of recent occluded person Re-ID methods on four popular datasets: Partial-ReID, Partial-iLIDS, Occluded-ReID, and Occluded-DukeMTMC.

Person Re-Identification

A Robust Ensemble Model for Patasitic Egg Detection and Classification

no code implementations4 Jul 2022 Yuqi Wang, Zhiqiang He, Shenghui Huang, Huabin Du

Intestinal parasitic infections, as a leading causes of morbidity worldwide, still lacks time-saving, high-sensitivity and user-friendly examination method.

Classification Data Augmentation +1

mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation

1 code implementation6 Jun 2022 Yao Zhang, Nanjun He, Jiawei Yang, Yuexiang Li, Dong Wei, Yawen Huang, Yang Zhang, Zhiqiang He, Yefeng Zheng

Concretely, we propose a novel multimodal Medical Transformer (mmFormer) for incomplete multimodal learning with three main components: the hybrid modality-specific encoders that bridge a convolutional encoder and an intra-modal Transformer for both local and global context modeling within each modality; an inter-modal Transformer to build and align the long-range correlations across modalities for modality-invariant features with global semantics corresponding to tumor region; a decoder that performs a progressive up-sampling and fusion with the modality-invariant features to generate robust segmentation.

Brain Tumor Segmentation Segmentation +1

Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images

no code implementations26 May 2022 Yao Zhang, Jiawei Yang, Yang Liu, Jiang Tian, Siyun Wang, Cheng Zhong, Zhongchao shi, Yang Zhang, Zhiqiang He

In this paper, we propose a Decoupled Pyramid Correlation Network (DPC-Net) that exploits attention mechanisms to fully leverage both low- and high-level features embedded in FCN to segment liver tumor.

Computed Tomography (CT) Image Segmentation +3

Designing the Topology of Graph Neural Networks: A Novel Feature Fusion Perspective

1 code implementation29 Dec 2021 Lanning Wei, Huan Zhao, Zhiqiang He

To enjoy the benefits while alleviating the corresponding deficiencies of these two manners, we learn to design the topology of GNNs in a novel feature fusion perspective which is dubbed F$^2$GNN.

feature selection Neural Architecture Search

Learn Layer-wise Connections in Graph Neural Networks

no code implementations27 Dec 2021 Lanning Wei, Huan Zhao, Zhiqiang He

In recent years, Graph Neural Networks (GNNs) have shown superior performance on diverse applications on real-world datasets.

Neural Architecture Search

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).

Pooling Architecture Search for Graph Classification

2 code implementations24 Aug 2021 Lanning Wei, Huan Zhao, Quanming Yao, Zhiqiang He

To address this problem, we propose to use neural architecture search (NAS) to search for adaptive pooling architectures for graph classification.

Graph Classification Neural Architecture Search

TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation

1 code implementation21 Jul 2021 Jiawei Yang, Yao Zhang, Yuan Liang, Yang Zhang, Lei He, Zhiqiang He

Experiments on kidney tumor segmentation task demonstrate that TumorCP surpasses the strong baseline by a remarkable margin of 7. 12% on tumor Dice.

Data Augmentation Tumor Segmentation

Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation

2 code implementations21 Jul 2021 Yao Zhang, Jiawei Yang, Jiang Tian, Zhongchao shi, Cheng Zhong, Yang Zhang, Zhiqiang He

To this end, we propose a novel mutual learning (ML) strategy for effective and robust multi-modal liver tumor segmentation.

Computed Tomography (CT) Image Segmentation +3

ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities

2 code implementations28 Jun 2021 Yixin Wang, Yang Zhang, Yang Liu, Zihao Lin, Jiang Tian, Cheng Zhong, Zhongchao shi, Jianping Fan, Zhiqiang He

Specifically, ACN adopts a novel co-training network, which enables a coupled learning process for both full modality and missing modality to supplement each other's domain and feature representations, and more importantly, to recover the `missing' information of absent modalities.

Brain Tumor Segmentation Transfer Learning +1

Trust It or Not: Confidence-Guided Automatic Radiology Report Generation

no code implementations21 Jun 2021 Yixin Wang, Zihao Lin, Zhe Xu, Haoyu Dong, Jiang Tian, Jie Luo, Zhongchao shi, Yang Zhang, Jianping Fan, Zhiqiang He

Experimental results have demonstrated that the proposed method for model uncertainty characterization and estimation can produce more reliable confidence scores for radiology report generation, and the modified loss function, which takes into account the uncertainties, leads to better model performance on two public radiology report datasets.

Decision Making Image Captioning +1

Efficient Graph Neural Architecture Search

no code implementations1 Jan 2021 Huan Zhao, Lanning Wei, Quanming Yao, Zhiqiang He

To obtain state-of-the-art (SOAT) data-specific GNN architectures, researchers turn to the neural architecture search (NAS) methods.

Neural Architecture Search Transfer Learning

Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer

1 code implementation29 Dec 2020 Yao Zhang, Jiawei Yang, Feng Hou, Yang Liu, Yixin Wang, Jiang Tian, Cheng Zhong, Yang Zhang, Zhiqiang He

Accurate segmentation of cardiac structures can assist doctors to diagnose diseases, and to improve treatment planning, which is highly demanded in the clinical practice.

Image Segmentation Segmentation +2

Double-Uncertainty Weighted Method for Semi-supervised Learning

no code implementations19 Oct 2020 Yixin Wang, Yao Zhang, Jiang Tian, Cheng Zhong, Zhongchao shi, Yang Zhang, Zhiqiang He

We train the teacher model using Bayesian deep learning to obtain double-uncertainty, i. e. segmentation uncertainty and feature uncertainty.


Semantic Feature Attention Network for Liver Tumor Segmentation in Large-scale CT database

no code implementations1 Nov 2019 Yao Zhang, Cheng Zhong, Yang Zhang, Zhongchao shi, Zhiqiang He

In the SFAN, a Semantic Attention Transmission (SAT) module is designed to select discriminative low-level localization details with the guidance of neighboring high-level semantic information.

Computed Tomography (CT) Segmentation +1

Image Co-segmentation via Multi-scale Local Shape Transfer

no code implementations15 May 2018 Wei Teng, Yu Zhang, Xiaowu Chen, Jia Li, Zhiqiang He

Image co-segmentation is a challenging task in computer vision that aims to segment all pixels of the objects from a predefined semantic category.

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