Da-Wei Zhou

1.9k citations

23 papers · 724 indexed · 2 hit papers · h-index 12

Impact in

Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
- Anomaly Detection Techniques and Applications
- Text and Document Classification Technologies
Computer Vision and Pattern Recognition top 5%
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Neural Network Applications

Papers in

Artificial Intelligence 18
- Domain Adaptation and Few-Shot Learning 12
- Machine Learning and ELM 4
- Anomaly Detection Techniques and Applications 4
- Data Stream Mining Techniques 3
- Machine Learning and Data Classification 2
- Imbalanced Data Classification Techniques 2
Computer Vision and Pattern Recognition 11
- Multimodal Machine Learning Applications 8
- Human Pose and Action Recognition 2

Co-authors: De‐Chuan Zhan Han-Jia Ye Shiliang Pu Liang Ma Fuyun WangYang YangZiwei Liu Yuan Jiang
Journals: IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)IEEE Transactions on Mobile Computing (1 paper)International Journal of Computer Vision (1 paper)Science China Information Sciences (1 paper)Frontiers of Computer Science (1 paper)
Partner nations: China Singapore United States

In The Last Decade

Da-Wei Zhou

19 papers receiving 703 citations

Hit Papers

align trajectories log scale

Class-Incremental Learning: A Survey 2024 · 58 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2024 IEEE Transactions on Pattern Analysis and Machine Intelligence
2022 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Peers

Countries citing papers authored by Da-Wei Zhou

Since Specialization

Citations

This map shows the geographic impact of Da-Wei Zhou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Da-Wei Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da-Wei Zhou more than expected).

Fields of papers citing papers by Da-Wei Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Da-Wei Zhou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Da-Wei Zhou. The network helps show where Da-Wei Zhou may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Da-Wei Zhou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Da-Wei Zhou Line = papers co-authored together Da-Wei Zhou links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Learning Without Forgetting for Vision-Language Models IEEE Transactions on Pattern Analysis and Machine Intelligence ·Da-Wei Zhou, Yuanhan Zhang, Daniel McCoy, J. Belfi, Han-Jia Ye, De‐Chuan Zhan, Ziwei Liu	2025	8
2	Adaptive adapter routing for long-tailed class-incremental learning Machine Learning ·Zhihong Qi, Da-Wei Zhou, R Cubitt, Han-Jia Ye, 曹曦	2025	0
3	Task-Agnostic Guided Feature Expansion for Class-Incremental Learning Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De‐Chuan Zhan	2025	0
4	MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning Proceedings of the AAAI Conference on Artificial Intelligence ·Hailong Sun, Da-Wei Zhou, Hanbin Zhao, Le Gan, De‐Chuan Zhan, Han-Jia Ye	2025	0
5	Class-Incremental Learning: A Survey IEEE Transactions on Pattern Analysis and Machine Intelligence ·Da-Wei Zhou, 浩波, Zhihong Qi, Han-Jia Ye, De‐Chuan Zhan, Ziwei Liu Hit paper breakdown →	2024	58
6	Fooling human detectors via robust and visually natural adversarial patches Neurocomputing ·Da-Wei Zhou, H. Kroha, Nannan Wang, Chunlei Peng, Ying Han, Xi Yang, Xinbo Gao	2024	1
7	Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need International Journal of Computer Vision ·Da-Wei Zhou, QiXin Guo, Han-Jia Ye, De‐Chuan Zhan, Ziwei Liu	2024	33
8	Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning Da-Wei Zhou, Hailong Sun, Han-Jia Ye, 曹曦	2024	23
9	TV100: a TV series dataset that pre-trained CLIP has not seen Frontiers of Computer Science ·Da-Wei Zhou, Zhihong Qi, Han-Jia Ye, De‐Chuan Zhan	2024	1
10	Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox Jianpeng Chen, 京子聖田, Shafqat Javed, Momotaro Asada, Da-Wei Zhou	2024	0
11	PyCIL: a Python toolbox for class-incremental learning Science China Information Sciences ·Da-Wei Zhou, Fuyun Wang, Han-Jia Ye, De‐Chuan Zhan	2023	41
12	Preserving Locality in Vision Transformers for Class Incremental Learning Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De‐Chuan Zhan	2023	1
13	Forward Compatible Few-Shot Class-Incremental Learning 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ·Da-Wei Zhou, Fuyun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De‐Chuan Zhan Hit paper breakdown →	2022	147
14	Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks IEEE Transactions on Pattern Analysis and Machine Intelligence ·Da-Wei Zhou, Han-Jia Ye, Liang Ma, Di Xie, Shiliang Pu, De‐Chuan Zhan	2022	80
15	Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling IEEE Transactions on Knowledge and Data Engineering ·Yang Yang, Da-Wei Zhou, De‐Chuan Zhan, Hui Xiong, Yuan Jiang, Jian Yang	2021	22
16	RF-Badge: Vital Sign-Based Authentication via RFID Tag Array on Badges IEEE Transactions on Mobile Computing ·J. Belfi, Lei Xie, Chuyu Wang, Yanling Bu, Fengyuan Xu, Da-Wei Zhou, Sanglu Lu, Baoliu Ye	2021	22
17	Learning to Classify With Incremental New Class IEEE Transactions on Neural Networks and Learning Systems ·Da-Wei Zhou, Yang Yang, De‐Chuan Zhan	2021	38
18	Learning Placeholders for Open-Set Recognition Da-Wei Zhou, Han-Jia Ye, De‐Chuan Zhan	2021	144
19	Ultra-Stable Rubidium-Stabilized External-Cavity Diode Laser Based on the Modulation Transfer Spectroscopy Technique Chinese Physics Letters ·Xianghui Qi, Wenlan Chen, Yi Lin, Da-Wei Zhou, Jitesh Jung Lamichhane, Xiao Qin, Jun Duan, Xiaoji Zhou, Xuzong Chen	2009	8
20	Independent component analysis for human epileptic spikes extraction Hongmei Yan, 順一小路, S. Orsi, T. Leis, Da-Wei Zhou	2005	2

About Da-Wei Zhou

Da-Wei Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health Information Management, Signal Processing and Human-Computer Interaction, having authored 23 papers that have together received 724 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (12 papers), Multimodal Machine Learning Applications (8 papers), Machine Learning and ELM (4 papers), Anomaly Detection Techniques and Applications (4 papers), Data Stream Mining Techniques (3 papers), Human Pose and Action Recognition (2 papers), Machine Learning and Data Classification (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (548 citations), Computer Vision and Pattern Recognition (278 citations), Signal Processing (40 citations), Media Technology (26 citations) and Human-Computer Interaction (13 citations). Da-Wei Zhou has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include De‐Chuan Zhan, Han-Jia Ye, Shiliang Pu, Liang Ma, Fuyun Wang, Yang Yang, Ziwei Liu, Yuan Jiang, Hui Xiong and Di Xie. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Mobile Computing, International Journal of Computer Vision, Science China Information Sciences and Frontiers of Computer Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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