Kevin Lin

1.2k total citations · 1 hit paper
12 papers, 655 citations indexed

About

Kevin Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Kevin Lin has authored 12 papers receiving a total of 655 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Aerospace Engineering. Recurrent topics in Kevin Lin's work include Advanced Image and Video Retrieval Techniques (7 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Robotics and Sensor-Based Localization (4 papers). Kevin Lin is often cited by papers focused on Advanced Image and Video Retrieval Techniques (7 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Robotics and Sensor-Based Localization (4 papers). Kevin Lin collaborates with scholars based in Taiwan, United States and United Kingdom. Kevin Lin's co-authors include Chu‐Song Chen, Huei‐Fang Yang, Jiwen Lu, Jie Zhou, Ming–Ting Sun, Jen-Hao Hsiao, Kuan-Hsien Liu, Kun Luo, Yinpeng Chen and Zicheng Liu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Kevin Lin

12 papers receiving 642 citations

Hit Papers

Learning Compact Binary Descriptors with Unsupervised Dee... 2016 2026 2019 2022 2016 50 100 150 200 250
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. Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks
    2016 257 citations Kevin Lin, Jiwen Lu et al. profile →

Peers

Kevin Lin
Kaiqi Huang China
Fazhi He China
Wei Tong China
Yuxuan Wei China
Yanbing Xue China
Jinlong Shi China
Long Zhu United States
Chenxin Tao China
Kaiqi Huang China
Kevin Lin
Citations per year, relative to Kevin Lin Kevin Lin (= 1×) peers Kaiqi Huang

Countries citing papers authored by Kevin Lin

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Lin. A scholar is included among the top collaborators of Kevin Lin 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 Kevin Lin. Kevin Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Wang, Jianfeng, et al.. (2025). LiVOS: Light Video Object Segmentation with Gated Linear Matching. 8668–8678. 1 indexed citations
2.
Lin, Kevin, et al.. (2023). MetaEx-GAN: Meta Exploration to Improve Natural Language Generation via Generative Adversarial Networks. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 3968–3980. 2 indexed citations
3.
4.
Lin, Kevin, Lijuan Wang, Kun Luo, et al.. (2020). Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. 31(3). 1066–1078. 50 indexed citations
5.
Lin, Kevin, Lijuan Wang, Kun Luo, et al.. (2019). Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation.. arXiv (Cornell University). 3 indexed citations
6.
Yang, Huei‐Fang, et al.. (2019). Cross-Batch Reference Learning for Deep Retrieval. IEEE Transactions on Neural Networks and Learning Systems. 31(9). 3145–3158. 3 indexed citations
7.
Lin, Kevin, Jiwen Lu, Chu‐Song Chen, Jie Zhou, & Ming–Ting Sun. (2018). Unsupervised Deep Learning of Compact Binary Descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(6). 1501–1514. 51 indexed citations
8.
Yang, Huei‐Fang, Kevin Lin, & Chu‐Song Chen. (2017). Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(2). 437–451. 224 indexed citations
9.
Lin, Kevin, Jiwen Lu, Chu‐Song Chen, & Jie Zhou. (2016). Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks. 1183–1192. 257 indexed citations breakdown →
10.
Yang, Huei‐Fang, Kevin Lin, & Chu‐Song Chen. (2016). Cross-batch Reference Learning for Deep Classification and Retrieval. 1237–1246. 12 indexed citations
11.
Lin, Kevin, Huei‐Fang Yang, Kuan-Hsien Liu, Jen-Hao Hsiao, & Chu‐Song Chen. (2015). Rapid Clothing Retrieval via Deep Learning of Binary Codes and Hierarchical Search. 499–502. 48 indexed citations
12.
Lin, Shih-Yao, et al.. (2013). Teleport. 1–1. 1 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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