Search Results for author: Zeng Zeng

Found 39 papers, 12 papers with code

A Deeply Supervised Semantic Segmentation Method Based on GAN

no code implementations6 Oct 2023 Wei Zhao, Qiyu Wei, Zeng Zeng

In recent years, the field of intelligent transportation has witnessed rapid advancements, driven by the increasing demand for automation and efficiency in transportation systems.

Generative Adversarial Network Segmentation +2

Wafer Map Defect Patterns Semi-Supervised Classification Using Latent Vector Representation

no code implementations6 Oct 2023 Qiyu Wei, Wei Zhao, Xiaoyan Zheng, Zeng Zeng

In this paper, we propose a method that initially employs a pre-trained VAE model to obtain the fault distribution information of the wafer map.

Defect Detection

SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein-Protein Interaction Prediction

no code implementations15 May 2023 Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, XiaoLi Li

Protein-protein interactions (PPIs) are crucial in various biological processes and their study has significant implications for drug development and disease diagnosis.

Graph Learning Graph Neural Network

Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation

no code implementations11 May 2023 Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan, S. Kevin Zhou

To achieve efficient few-shot cross-modality segmentation, we propose a novel transformation-consistent meta-hallucination framework, meta-hallucinator, with the goal of learning to diversify data distributions and generate useful examples for enhancing cross-modality performance.

Cardiac Segmentation Hallucination +6

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

1 code implementation5 Dec 2022 Ziyuan Zhao, Fangcheng Zhou, Kaixin Xu, Zeng Zeng, Cuntai Guan, S. Kevin Zhou

To assess the effectiveness of our method, we conduct extensive experiments on two different tasks for cross-modality segmentation between MRI and CT images.

Image Segmentation Medical Image Segmentation +4

ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation

1 code implementation5 Jul 2022 Ziyuan Zhao, Andong Zhu, Zeng Zeng, Bharadwaj Veeravalli, Cuntai Guan

While deep models have shown promising performance in medical image segmentation, they heavily rely on a large amount of well-annotated data, which is difficult to access, especially in clinical practice.

Image Segmentation Knowledge Distillation +3

Residual Channel Attention Network for Brain Glioma Segmentation

no code implementations22 May 2022 Yiming Yao, Peisheng Qian, Ziyuan Zhao, Zeng Zeng

A glioma is a malignant brain tumor that seriously affects cognitive functions and lowers patients' life quality.


Deep Feature Fusion via Graph Convolutional Network for Intracranial Artery Labeling

no code implementations22 May 2022 Yaxin Zhu, Peisheng Qian, Ziyuan Zhao, Zeng Zeng

Intracranial arteries are critical blood vessels that supply the brain with oxygenated blood.


Self-supervised Assisted Active Learning for Skin Lesion Segmentation

1 code implementation14 May 2022 Ziyuan Zhao, Wenjing Lu, Zeng Zeng, Kaixin Xu, Bharadwaj Veeravalli, Cuntai Guan

Label scarcity has been a long-standing issue for biomedical image segmentation, due to high annotation costs and professional requirements.

Active Learning Diversity +6

Adaptive Mean-Residue Loss for Robust Facial Age Estimation

1 code implementation31 Mar 2022 Ziyuan Zhao, Peisheng Qian, Yubo Hou, Zeng Zeng

Automated facial age estimation has diverse real-world applications in multimedia analysis, e. g., video surveillance, and human-computer interaction.

Age Estimation

MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels

1 code implementation23 Mar 2022 Ziyuan Zhao, Kaixin Xu, Shumeng Li, Zeng Zeng, Cuntai Guan

Although deep unsupervised domain adaptation (UDA) can leverage well-established source domain annotations and abundant target domain data to facilitate cross-modality image segmentation and also mitigate the label paucity problem on the target domain, the conventional UDA methods suffer from severe performance degradation when source domain annotations are scarce.

Image Segmentation Medical Image Segmentation +3

DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

1 code implementation22 Jan 2021 Ziyuan Zhao, Zeng Zeng, Kaixin Xu, Cen Chen, Cuntai Guan

We use the proposed criteria to select samples for strong and weak labelers to produce oracle labels and pseudo labels simultaneously at each active learning iteration in an ensemble learning manner, which can be examined with IoMT Platform.

Active Learning Ensemble Learning +2

Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning

no code implementations19 Jan 2021 Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng

We model the DL-PBS system from the perspective of CPS and use deep learning to predict the layout of bicycle parking spots and the dynamic demand of bicycle dispatching.

Multi-Objective Reinforcement Learning

Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

no code implementations19 Jan 2021 Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng

The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation.

Clustering Graph Neural Network +1

A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection

no code implementations29 May 2020 Jianxi Yang, Likai Zhang, Cen Chen, Yangfan Li, Ren Li, Guiping Wang, Shixin Jiang, Zeng Zeng

Specifically, CNN is utilized to model the spatial relations and the short-term temporal dependencies among sensors, while the output features of CNN are fed into the GRU to learn the long-term temporal dependencies jointly.

BIG-bench Machine Learning Image Classification +2

Multi-Instance Multi-Label Learning for Gene Mutation Prediction in Hepatocellular Carcinoma

no code implementations8 May 2020 Kaixin Xu, Ziyuan Zhao, Jiapan Gu, Zeng Zeng, Chan Wan Ying, Lim Kheng Choon, Thng Choon Hua, Pierce KH Chow

Gene mutation prediction in hepatocellular carcinoma (HCC) is of great diagnostic and prognostic value for personalized treatments and precision medicine.

Multi-Label Learning

Ordered or Orderless: A Revisit for Video based Person Re-Identification

no code implementations24 Dec 2019 Le Zhang, Zenglin Shi, Joey Tianyi Zhou, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Zeng Zeng, Chunhua Shen

Specifically, with a diagnostic analysis, we show that the recurrent structure may not be effective to learn temporal dependencies than what we expected and implicitly yields an orderless representation.

Video-Based Person Re-Identification

Cribriform pattern detection in prostate histopathological images using deep learning models

no code implementations9 Oct 2019 Malay Singh, Emarene Mationg Kalaw, Wang Jie, Mundher Al-Shabi, Chin Fong Wong, Danilo Medina Giron, Kian-Tai Chong, Maxine Tan, Zeng Zeng, Hwee Kuan Lee

In this paper, we present an annotated cribriform dataset along with analysis of deep learning models and hand-crafted features for cribriform pattern detection in prostate histopathological images.

Classification General Classification +1

Robust Regression via Deep Negative Correlation Learning

no code implementations24 Aug 2019 Le Zhang, Zenglin Shi, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Joey Tianyi Zhou, Guoyan Zheng, Zeng Zeng

Nonlinear regression has been extensively employed in many computer vision problems (e. g., crowd counting, age estimation, affective computing).

Age Estimation Crowd Counting +2

A Deep Framework for Bone Age Assessment based on Finger Joint Localization

no code implementations7 May 2019 Xiaoman Zhang, Ziyuan Zhao, Cen Chen, Songyou Peng, Min Wu, Zhongyao Cheng, Singee Teo, Le Zhang, Zeng Zeng

In this study, we applied powerful deep neural network and explored a process in the forecast of skeletal bone age with the specifically combine joints images to increase the performance accuracy compared with the whole hand images.

End-to-End Video Classification with Knowledge Graphs

no code implementations6 Nov 2017 Fang Yuan, Zhe Wang, Jie Lin, Luis Fernando D'Haro, Kim Jung Jae, Zeng Zeng, Vijay Chandrasekhar

In particular, we unify traditional "knowledgeless" machine learning models and knowledge graphs in a novel end-to-end framework.

BIG-bench Machine Learning Classification +4

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