Guna Seetharaman

4.7k total citations
139 papers, 2.1k citations indexed

About

Guna Seetharaman is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Guna Seetharaman has authored 139 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Computer Vision and Pattern Recognition, 33 papers in Aerospace Engineering and 26 papers in Artificial Intelligence. Recurrent topics in Guna Seetharaman's work include Advanced Vision and Imaging (35 papers), Video Surveillance and Tracking Methods (32 papers) and Advanced Image and Video Retrieval Techniques (28 papers). Guna Seetharaman is often cited by papers focused on Advanced Vision and Imaging (35 papers), Video Surveillance and Tracking Methods (32 papers) and Advanced Image and Video Retrieval Techniques (28 papers). Guna Seetharaman collaborates with scholars based in United States, India and France. Guna Seetharaman's co-authors include Kannappan Palaniappan, Filiz Bunyak, Erik Blasch, Bertrand Zavidovique, Syomantak Chaudhuri, Hadi Aliakbarpour, Rui Wang, Adel Hafiane, Arun Lakhotia and V. B. Surya Prasath and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Guna Seetharaman

132 papers receiving 2.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Guna Seetharaman 1.5k 410 404 312 167 139 2.1k
P. J. Narayanan 1.7k 1.1× 257 0.6× 310 0.8× 220 0.7× 250 1.5× 130 2.2k
Qiang Wang 1.6k 1.1× 328 0.8× 339 0.8× 218 0.7× 106 0.6× 162 2.3k
Mongi A. Abidi 1.7k 1.1× 257 0.6× 591 1.5× 501 1.6× 100 0.6× 172 2.5k
Alexander G. Schwing 1.9k 1.3× 830 2.0× 340 0.8× 299 1.0× 144 0.9× 88 2.8k
Bumsub Ham 1.9k 1.3× 754 1.8× 232 0.6× 483 1.5× 343 2.1× 62 2.5k
Robert Laganière 1.9k 1.3× 350 0.9× 759 1.9× 777 2.5× 55 0.3× 133 2.7k
Alexander Kirillov 1.7k 1.2× 664 1.6× 330 0.8× 237 0.8× 45 0.3× 22 2.6k
Georgios Tziritas 2.2k 1.5× 480 1.2× 223 0.6× 332 1.1× 103 0.6× 73 2.9k
Worthy N. Martin 899 0.6× 494 1.2× 232 0.6× 143 0.5× 87 0.5× 60 2.0k
Sung‐Eui Yoon 2.1k 1.4× 202 0.5× 305 0.8× 124 0.4× 150 0.9× 148 2.7k

Countries citing papers authored by Guna Seetharaman

Since Specialization
Citations

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

Fields of papers citing papers by Guna Seetharaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guna Seetharaman

This figure shows the co-authorship network connecting the top 25 collaborators of Guna Seetharaman. A scholar is included among the top collaborators of Guna Seetharaman 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 Guna Seetharaman. Guna Seetharaman 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.
Palaniappan, Kannappan, et al.. (2023). DeepFTSG: Multi-stream Asymmetric USE-Net Trellis Encoders with Shared Decoder Feature Fusion Architecture for Video Motion Segmentation. International Journal of Computer Vision. 132(3). 776–804. 6 indexed citations
2.
Gao, Ke, et al.. (2020). Local Feature Performance Evaluation for Structure-From-Motion and Multi-View Stereo Using Simulated City-Scale Aerial Imagery. IEEE Sensors Journal. 21(10). 11615–11627. 16 indexed citations
3.
Al-Shakarji, Noor, Filiz Bunyak, Hadi Aliakbarpour, Guna Seetharaman, & Kannappan Palaniappan. (2019). Multi-Cue Vehicle Detection for Semantic Video Compression in Georegistered Aerial Videos. arXiv (Cornell University). 56–65. 1 indexed citations
4.
Aliakbarpour, Hadi, et al.. (2018). Performance Evaluation of Feature Descriptors for Aerial Imagery Mosaicking. 1–7. 3 indexed citations
5.
Peng, Jing, Alexander Aved, Guna Seetharaman, & Kannappan Palaniappan. (2017). Multiview Boosting With Information Propagation for Classification. IEEE Transactions on Neural Networks and Learning Systems. 29(3). 657–669. 18 indexed citations
6.
Prasath, V. B. Surya, et al.. (2014). Elastic Body Spline Based Image Segmentation. Figshare. 6 indexed citations
7.
Liang, Pengpeng, Haibin Ling, Erik Blasch, et al.. (2013). Vehicle detection in wide area aerial surveillance using Temporal Context. International Conference on Information Fusion. 181–188. 27 indexed citations
8.
Peng, Jing & Guna Seetharaman. (2013). Combining the advice of experts with randomized boosting for robust pattern recognition. 1 indexed citations
9.
Pelapur, Rengarajan, Sema Candemir, Filiz Bunyak, et al.. (2012). Persistent target tracking using likelihood fusion in wide-area and full motion video sequences. International Conference on Information Fusion. 2420–2427. 51 indexed citations
10.
Blasch, Erik, Haibin Ling, Yi Wu, et al.. (2012). Dismount tracking and identification from electro-optical imagery. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8402. 84020H–84020H. 9 indexed citations
11.
Palaniappan, Kannappan, Ilker Ersoy, Guna Seetharaman, et al.. (2011). Parallel flux tensor analysis for efficient moving object detection. International Conference on Information Fusion. 1–8. 13 indexed citations
12.
Pal, Debnath, et al.. (2008). Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments. Genome biology. 9(3). R52–R52. 15 indexed citations
13.
Seetharaman, Guna, Michael L. Talbert, & Erik Blasch. (2007). Architectural Elements of Integrated Micro-Sensors for Distributed Sensor Networks. 157–165.
14.
Talbert, Michael L. & Guna Seetharaman. (2006). When sensor Webs start being taken seriously. 1. 200–207. 1 indexed citations
15.
Kannan, Rajgopal, et al.. (2005). Analysis of communication vulnerability through misbehavior in wireless and sensor networks. Civil War Book Review. 2. 1040–1046 Vol. 2. 4 indexed citations
16.
Seetharaman, Guna, et al.. (2004). Accurate modeling of thin-film inductance for nano-chip. 2. 351–355. 2 indexed citations
17.
Seetharaman, Guna, et al.. (2004). FPGA implementable architecture for geometric global positioning. 75. 451–455. 1 indexed citations
18.
Chaudhuri, Subhasis, et al.. (2002). Content Based Image Retrieval Using Motif Cooccurence Matrix.. 8 indexed citations
19.
Seetharaman, Guna, et al.. (2002). Video-Assisted Global Positioning in Terrain Navigation: Hough Transform Solution..
20.
Seetharaman, Guna. (1994). Image sequence analysis for three-dimensional perception of dynamic scenes. 361–403. 9 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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