Yilin Yan

1.9k total citations · 1 hit paper
23 papers, 1.3k citations indexed

About

Yilin Yan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Yilin Yan has authored 23 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 5 papers in Information Systems. Recurrent topics in Yilin Yan's work include Anomaly Detection Techniques and Applications (7 papers), Imbalanced Data Classification Techniques (5 papers) and Data Stream Mining Techniques (3 papers). Yilin Yan is often cited by papers focused on Anomaly Detection Techniques and Applications (7 papers), Imbalanced Data Classification Techniques (5 papers) and Data Stream Mining Techniques (3 papers). Yilin Yan collaborates with scholars based in United States, China and Taiwan. Yilin Yan's co-authors include Mei‐Ling Shyu, Shu‐Ching Chen, Saad Sadiq, Yudong Tao, Haiman Tian, Samira Pouyanfar, S. S. Iyengar, Maria Presa Reyes, Min Chen and Long Yu and has published in prestigious journals such as ACM Computing Surveys, Journal of Chemometrics and Journal of Visual Communication and Image Representation.

In The Last Decade

Yilin Yan

23 papers receiving 1.2k citations

Hit Papers

align trajectories

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.

A Survey on Deep Learning

2018 915 citations Samira Pouyanfar, Saad Sadiq et al. ACM Computing Surveys profile →

Peers

Yilin Yan

AI

CVPR

CNC

IS

EEE

Saad Sadiq United States

Haiman Tian United States

Yun Li China

Muhammad Atif Tahir United Kingdom

Rocío Aláiz-Rodríguez Spain

Maria Presa Reyes United States

Jiejun Xu United States

Daniel Urda Spain

Samina Khalid Pakistan

Saad Sadiq United States

Yilin Yan

495 ×0.8

AI

291 ×0.8

CVPR

123 ×1.0

CNC

102 ×0.8

IS

97 ×0.9

EEE

Citations per year, relative to Yilin Yan Yilin Yan (= 1×) peers Saad Sadiq

Countries citing papers authored by Yilin Yan

Since Specialization

Citations

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

Fields of papers citing papers by Yilin Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yilin Yan

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

All Works

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

20 of 20 papers shown

1.

Xiong, Taisong, et al.. (2022). Radar Echo Spatiotemporal Sequence Prediction Using an Improved ConvGRU Deep Learning Model. Atmosphere. 13(1). 88–88. 12 indexed citations

2.

Yan, Yilin, Samira Pouyanfar, Yudong Tao, et al.. (2020). Florida International University - University of Miami Trecvid 2014. 2 indexed citations

3.

Pouyanfar, Samira, Saad Sadiq, Yilin Yan, et al.. (2018). A Survey on Deep Learning. ACM Computing Surveys. 51(5). 1–36. 915 indexed citations breakdown →

4.

Yu, Long, Xia Sun, Shengwei Tian, Xinyu Shi, & Yilin Yan. (2018). Drug and Nondrug Classification Based on Deep Learning with Various Feature Selection Strategies. Current Bioinformatics. 13(3). 253–259. 55 indexed citations

5.

Yan, Yilin, Min Chen, Saad Sadiq, & Mei‐Ling Shyu. (2017). Efficient Imbalanced Multimedia Concept Retrieval by Deep Learning on Spark Clusters. RePEc: Research Papers in Economics. 8(1). 1–20. 19 indexed citations

6.

Sadiq, Saad, et al.. (2017). AAFA: Associative Affinity Factor Analysis for Bot Detection and Stance Classification in Twitter. 3. 356–365. 13 indexed citations

7.

Sadiq, Saad, Yudong Tao, Yilin Yan, & Mei‐Ling Shyu. (2017). Mining Anomalies in Medicare Big Data Using Patient Rule Induction Method. 185–192. 25 indexed citations

8.

Sadiq, Saad, Yilin Yan, Mei‐Ling Shyu, Shu‐Ching Chen, & Hemant Ishwaran. (2016). Enhancing Multimedia Imbalanced Concept Detection Using VIMP in Random Forests. PubMed. 2016. 601–608. 8 indexed citations

9.

Yan, Yilin & Mei‐Ling Shyu. (2016). Enhancing Rare Class Mining in Multimedia Big Data by Concept Correlation. 3. 281–286. 3 indexed citations

10.

Yan, Yilin, Samira Pouyanfar, Haiman Tian, et al.. (2016). Domain Knowledge Assisted Data Processing for Florida Public Hurricane Loss Model (Invited Paper). 6. 441–447. 3 indexed citations

11.

Yan, Yilin, et al.. (2016). Supporting Semantic Concept Retrieval with Negative Correlations in a Multimedia Big Data Mining System. International Journal of Semantic Computing. 10(2). 247–267. 7 indexed citations

12.

Yan, Yilin, et al.. (2016). Negative Correlation Discovery for Big Multimedia Data Semantic Concept Mining and Retrieval. 55–62. 9 indexed citations

13.

Hsieh, Jun-Wei, et al.. (2015). Modeling and recognizing action contexts in persons using sparse representation. Journal of Visual Communication and Image Representation. 30. 252–265. 6 indexed citations

14.

Yan, Yilin, Min Chen, Mei‐Ling Shyu, & Shu‐Ching Chen. (2015). Deep Learning for Imbalanced Multimedia Data Classification. 483–488. 116 indexed citations

15.

Hsieh, Jun-Wei, et al.. (2015). PLSA-based sparse representation for vehicle color classification. 1–6. 1 indexed citations

16.

Yan, Yilin, et al.. (2015). Spatio-Temporal Analysis for Human Action Detection and Recognition in Uncontrolled Environments. RePEc: Research Papers in Economics. 6(1). 1–18. 30 indexed citations

17.

Li, Weiming, Yilin Yan, Hao Tu, & Jia Xu. (2014). A dynamic taint tracking based method to detect sensitive information leaking. 45. 1–4. 1 indexed citations

18.

Meng, Tao, Yang Liu, Mei‐Ling Shyu, Yilin Yan, & Chi‐Min Shu. (2014). Enhancing Multimedia Semantic Concept Mining and Retrieval by Incorporating Negative Correlations. 7. 28–35. 9 indexed citations

19.

Yan, Yilin, Yang Liu, Mei‐Ling Shyu, & Min Chen. (2014). Utilizing concept correlations for effective imbalanced data classification. 561–568. 17 indexed citations

20.

Yan, Yilin, et al.. (2013). Sparse representation for recognizing object-to-object actions under occlusions. 117–120. 2 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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