Siwei Feng

1.4k total citations · 1 hit paper
27 papers, 927 citations indexed

About

Siwei Feng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Siwei Feng has authored 27 papers receiving a total of 927 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 7 papers in Media Technology. Recurrent topics in Siwei Feng's work include Remote-Sensing Image Classification (7 papers), Privacy-Preserving Technologies in Data (6 papers) and Image Retrieval and Classification Techniques (6 papers). Siwei Feng is often cited by papers focused on Remote-Sensing Image Classification (7 papers), Privacy-Preserving Technologies in Data (6 papers) and Image Retrieval and Classification Techniques (6 papers). Siwei Feng collaborates with scholars based in United States, China and Singapore. Siwei Feng's co-authors include R. Manmatha, Victor Lavrenko, Marco F. Duarte, M. Parente, Yuki Itoh, Han Yu, Qingguo Wei, Boyang Li, Yang Liu and Qiang Yang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Geoscience and Remote Sensing and Expert Systems with Applications.

In The Last Decade

Siwei Feng

24 papers receiving 882 citations

Hit Papers

Multiple Bernoulli relevance models for image and video a... 2004 2026 2011 2018 2004 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Multiple Bernoulli relevance models for image and video annotation
    2004 552 citations Siwei Feng, R. Manmatha et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Siwei Feng United States 11 700 289 171 58 39 27 927
Shudong Huang China 16 837 1.2× 561 1.9× 202 1.2× 45 0.8× 17 0.4× 32 1.1k
Chen Gong China 11 597 0.9× 440 1.5× 89 0.5× 66 1.1× 10 0.3× 16 866
Hangzai Luo China 17 850 1.2× 246 0.9× 138 0.8× 82 1.4× 13 0.3× 88 1.0k
Yuchi Huang United States 10 542 0.8× 211 0.7× 82 0.5× 54 0.9× 10 0.3× 16 702
Sanqiang Zhao Australia 11 840 1.2× 331 1.1× 152 0.9× 193 3.3× 14 0.4× 24 1.2k
Xinwen Hou China 15 722 1.0× 189 0.7× 224 1.3× 57 1.0× 8 0.2× 43 914
Guorong Xuan China 16 1.1k 1.5× 137 0.5× 85 0.5× 85 1.5× 7 0.2× 34 1.2k

Countries citing papers authored by Siwei Feng

Since Specialization
Citations

This map shows the geographic impact of Siwei Feng'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 Siwei Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siwei Feng more than expected).

Fields of papers citing papers by Siwei Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Siwei Feng. 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 Siwei Feng. The network helps show where Siwei Feng may publish in the future.

Co-authorship network of co-authors of Siwei Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Siwei Feng. A scholar is included among the top collaborators of Siwei Feng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Siwei Feng. Siwei Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Deng, Tao, et al.. (2025). Mobility-aware decentralized federated learning with joint optimization of local iteration and leader selection for vehicular networks. Computer Networks. 263. 111232–111232. 3 indexed citations
2.
3.
Wu, Feng, et al.. (2025). Federated Class-Incremental Learning via Weighted Aggregation and Distillation. IEEE Internet of Things Journal. 12(12). 22489–22503.
4.
Feng, Siwei, et al.. (2024). MMVFL: A Simple Vertical Federated Learning Framework for Multi-Class Multi-Participant Scenarios. Sensors. 24(2). 619–619. 4 indexed citations
5.
Chen, Yuanlu, et al.. (2024). General Federated Class-Incremental Learning With Lightweight Generative Replay. IEEE Internet of Things Journal. 11(20). 33927–33939. 3 indexed citations
6.
7.
Yu, Han, et al.. (2022). Federated Learning for Personalized Humor Recognition. ACM Transactions on Intelligent Systems and Technology. 13(4). 1–18. 8 indexed citations
8.
Feng, Siwei. (2022). Vertical federated learning-based feature selection with non-overlapping sample utilization. Expert Systems with Applications. 208. 118097–118097. 32 indexed citations
9.
Feng, Siwei, Boyang Li, Han Yu, Yang Liu, & Qiang Yang. (2022). Semi-Supervised Federated Heterogeneous Transfer Learning. Knowledge-Based Systems. 252. 109384–109384. 29 indexed citations
10.
Feng, Siwei. (2021). Sparsity in Machine Learning: An Information Selecting Perspective. Scholarworks (University of Massachusetts Amherst).
11.
Gao, Kaizhou, Siwei Feng, & Jingjin Yu. (2021). On Minimizing the Number of Running Buffers for Tabletop Rearrangement. 14 indexed citations
12.
Feng, Siwei. (2021). Wavelet-Based Non-Homogeneous Hidden Markov Chain Model For Hyperspectral Signature Classification. Scholarworks (University of Massachusetts Amherst).
13.
Feng, Siwei & Marco F. Duarte. (2018). Graph Regularized Autoencoder-Based Unsupervised Feature Selection. 2018 52nd Asilomar Conference on Signals, Systems, and Computers. 55–59. 5 indexed citations
14.
Feng, Siwei & Marco F. Duarte. (2018). Graph autoencoder-based unsupervised feature selection with broad and local data structure preservation. Neurocomputing. 312. 310–323. 36 indexed citations
15.
Feng, Siwei, Yuki Itoh, M. Parente, & Marco F. Duarte. (2017). Hyperspectral Band Selection From Statistical Wavelet Models. IEEE Transactions on Geoscience and Remote Sensing. 55(4). 2111–2123. 45 indexed citations
16.
Wei, Qingguo, et al.. (2016). Stimulus Specificity of Brain-Computer Interfaces Based on Code Modulation Visual Evoked Potentials. PLoS ONE. 11(5). e0156416–e0156416. 24 indexed citations
17.
Feng, Siwei, Marco F. Duarte, & M. Parente. (2015). Universality of wavelet-based non-homogeneous hidden Markov chain model features for hyperspectral signatures. 19–27. 6 indexed citations
18.
Itoh, Yuki, Siwei Feng, Marco F. Duarte, & M. Parente. (2014). Hyperspectral unmixing via semantic spectral representations. 149–152. 3 indexed citations
19.
Feng, Siwei, Yuki Itoh, M. Parente, & Marco F. Duarte. (2014). Tailoring non-homogeneous Markov chain wavelet models for hyperspectral signature classification. 5167–5171. 4 indexed citations
20.
Lavrenko, Victor, Siwei Feng, & R. Manmatha. (2004). Statistical models for automatic video annotation and retrieval. 3. iii–1044. 49 indexed citations

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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