Raghuraman Gopalan

2.9k total citations · 2 hit papers
17 papers, 1.7k citations indexed

About

Raghuraman Gopalan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Raghuraman Gopalan has authored 17 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Raghuraman Gopalan's work include Domain Adaptation and Few-Shot Learning (8 papers), Human Pose and Action Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Raghuraman Gopalan is often cited by papers focused on Domain Adaptation and Few-Shot Learning (8 papers), Human Pose and Action Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Raghuraman Gopalan collaborates with scholars based in United States and Japan. Raghuraman Gopalan's co-authors include Rama Chellappa, Ruonan Li, Vishal M. Patel, Tsai Hong Hong, Michael Shneier, Sumit Chopra, S. Balakrishnan, David Jacobs, Sima Taheri and Pavan Turaga and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Raghuraman Gopalan

17 papers receiving 1.7k citations

Hit Papers

Domain adaptation for object recognition: An unsupervised... 2011 2026 2016 2021 2011 2015 200 400 600
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. Domain adaptation for object recognition: An unsupervised approach
    2011 666 citations Raghuraman Gopalan, Ruonan Li et al. profile →
  2. Visual Domain Adaptation: A survey of recent advances
    2015 569 citations Vishal M. Patel, Raghuraman Gopalan et al. IEEE Signal Processing Magazine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raghuraman Gopalan United States 9 1.1k 1.1k 156 131 122 17 1.7k
Ruonan Li China 14 1.2k 1.1× 1.1k 1.0× 125 0.8× 126 1.0× 48 0.4× 49 2.0k
Xiangyu Yue United States 16 849 0.8× 1.3k 1.3× 126 0.8× 46 0.4× 145 1.2× 36 2.4k
Baochen Sun United States 6 942 0.9× 812 0.8× 100 0.6× 111 0.8× 19 0.2× 8 1.6k
Zhangjie Cao China 19 2.1k 1.9× 1.9k 1.8× 169 1.1× 192 1.5× 140 1.1× 35 3.4k
Yingwei Pan China 29 1.4k 1.3× 3.3k 3.2× 162 1.0× 56 0.4× 38 0.3× 85 4.0k
BoRui Wu United States 17 1.3k 1.1× 1.9k 1.8× 146 0.9× 17 0.1× 108 0.9× 42 2.8k
Joanna Materzyńska Mexico 6 1.1k 1.0× 2.0k 1.9× 88 0.6× 33 0.3× 130 1.1× 6 2.3k
Konstantinos Bousmalis United Kingdom 9 783 0.7× 1.0k 1.0× 126 0.8× 52 0.4× 16 0.1× 16 1.5k
Yuan Shi China 10 1.3k 1.2× 928 0.9× 109 0.7× 163 1.2× 10 0.1× 28 1.8k
Germán Ros Spain 6 609 0.6× 1.3k 1.2× 269 1.7× 25 0.2× 154 1.3× 12 1.7k

Countries citing papers authored by Raghuraman Gopalan

Since Specialization
Citations

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

Fields of papers citing papers by Raghuraman Gopalan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raghuraman Gopalan

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

All Works

17 of 17 papers shown
1.
Gopalan, Raghuraman, Ruonan Li, Vishal M. Patel, & Rama Chellappa. (2015). Domain Adaptation for Visual Recognition. 8(4). 285–378. 21 indexed citations
2.
Gopalan, Raghuraman. (2015). Hierarchical sparse coding with geometric prior for visual geo-location. 12. 2432–2439. 6 indexed citations
3.
Gopalan, Raghuraman, Ruonan Li, Vishal M. Patel, & Rama Chellappa. (2015). Domain Adaptation for Visual Recognition. now publishers, Inc. eBooks. 4 indexed citations
4.
Patel, Vishal M., Raghuraman Gopalan, Ruonan Li, & Rama Chellappa. (2015). Visual Domain Adaptation: A survey of recent advances. IEEE Signal Processing Magazine. 32(3). 53–69. 569 indexed citations breakdown →
5.
Gopalan, Raghuraman, Ruonan Li, & Rama Chellappa. (2014). Unsupervised Adaptation Across Domain Shifts by Generating Intermediate Data Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(11). 2288–2302. 136 indexed citations
6.
Ho, Huy Tho & Raghuraman Gopalan. (2014). Model-Driven Domain Adaptation on Product Manifolds for Unconstrained Face Recognition. International Journal of Computer Vision. 109(1-2). 110–125. 21 indexed citations
7.
Chopra, Sumit, S. Balakrishnan, & Raghuraman Gopalan. (2013). DLID: Deep learning for domain adaptation by interpolating between domains. 67 indexed citations
8.
Gopalan, Raghuraman. (2013). Joint Sparsity-Based Representation and Analysis of Unconstrained Activities. 17. 2738–2745. 4 indexed citations
9.
Zavesky, Eric, et al.. (2013). VidCat: an image and video analysis service for personal media management. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8667. 86670F–86670F. 4 indexed citations
10.
Gopalan, Raghuraman. (2013). Learning Cross-Domain Information Transfer for Location Recognition and Clustering. 31. 731–738. 4 indexed citations
11.
Gopalan, Raghuraman, Sima Taheri, Pavan Turaga, & Rama Chellappa. (2012). A Blur-Robust Descriptor with Applications to Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(6). 1220–1226. 51 indexed citations
12.
Gopalan, Raghuraman, Tsai Hong Hong, Michael Shneier, & Rama Chellappa. (2012). A Learning Approach Towards Detection and Tracking of Lane Markings. IEEE Transactions on Intelligent Transportation Systems. 13(3). 1088–1098. 134 indexed citations
13.
Gopalan, Raghuraman, Ruonan Li, & Rama Chellappa. (2011). Domain adaptation for object recognition: An unsupervised approach. 999–1006. 666 indexed citations breakdown →
14.
Gopalan, Raghuraman & Jagan Sankaranarayanan. (2011). Max-margin clustering: Detecting margins from projections of points on lines. 5. 2769–2776. 3 indexed citations
15.
Gopalan, Raghuraman & William Robson Schwartz. (2010). Detecting humans under partial occlusion using Markov logic networks. 182–186. 1 indexed citations
16.
Gopalan, Raghuraman & David Jacobs. (2009). Comparing and combining lighting insensitive approaches for face recognition. Computer Vision and Image Understanding. 114(1). 135–145. 27 indexed citations
17.
Gopalan, Raghuraman & Behzad Dariush. (2009). Toward a vision based hand gesture interface for robotic grasping. 1452–1459. 5 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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