Anindya Sarkar

851 total citations
20 papers, 440 citations indexed

About

Anindya Sarkar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Anindya Sarkar has authored 20 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 2 papers in Media Technology. Recurrent topics in Anindya Sarkar's work include AI in cancer detection (5 papers), Advanced Steganography and Watermarking Techniques (5 papers) and Digital Media Forensic Detection (5 papers). Anindya Sarkar is often cited by papers focused on AI in cancer detection (5 papers), Advanced Steganography and Watermarking Techniques (5 papers) and Digital Media Forensic Detection (5 papers). Anindya Sarkar collaborates with scholars based in United States, India and South Korea. Anindya Sarkar's co-authors include B.S. Manjunath, Kien Nguyen, Anil K. Jain, Lakshmanan Nataraj, Kaushal Solanki, Upamanyu Madhow, Vineeth N Balasubramanian, Uday Maitra, Ambuj K. Singh and Ramesh Kandanelli and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Dalton Transactions and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Anindya Sarkar

19 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anindya Sarkar United States 14 287 183 84 39 38 20 440
Xianling Hu China 6 156 0.5× 259 1.4× 190 2.3× 22 0.6× 42 1.1× 9 391
Manish Sapkota United States 6 205 0.7× 258 1.4× 126 1.5× 12 0.3× 43 1.1× 10 392
Mike Feldman United States 4 170 0.6× 267 1.5× 164 2.0× 15 0.4× 38 1.0× 4 395
Hammad Qureshi Pakistan 8 83 0.3× 167 0.9× 107 1.3× 19 0.5× 39 1.0× 24 321
Ju Han United States 13 220 0.8× 229 1.3× 86 1.0× 45 1.2× 83 2.2× 23 482
Ozan Ciga Canada 4 193 0.7× 387 2.1× 250 3.0× 14 0.4× 80 2.1× 4 484
Anton Böhm Germany 3 339 1.2× 430 2.3× 282 3.4× 32 0.8× 88 2.3× 5 586
Shazia Akbar United Kingdom 8 104 0.4× 150 0.8× 116 1.4× 46 1.2× 34 0.9× 20 269
Olivier Saidi United States 5 179 0.6× 286 1.6× 95 1.1× 15 0.4× 34 0.9× 10 383
Ying Xiao China 11 97 0.3× 190 1.0× 37 0.4× 34 0.9× 54 1.4× 41 451

Countries citing papers authored by Anindya Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Anindya Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anindya Sarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Anindya Sarkar. A scholar is included among the top collaborators of Anindya Sarkar 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 Anindya Sarkar. Anindya Sarkar 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.
Sarkar, Anindya, et al.. (2022). A Framework for Learning Ante-hoc Explainable Models via Concepts. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10276–10285. 24 indexed citations
2.
Sarkar, Anindya, et al.. (2022). Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3564–3573. 4 indexed citations
3.
Sarkar, Anindya, et al.. (2021). Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach. Neural Information Processing Systems. 34. 1 indexed citations
4.
Amgad, Mohamed, Anindya Sarkar, Rachel Redman, et al.. (2019). Joint region and nucleus segmentation for characterization of tumor infiltrating lymphocytes in breast cancer. PubMed. 10956. 20–20. 33 indexed citations
5.
Sarkar, Anindya, et al.. (2019). Zero-Shot Multilingual Sentiment Analysis using Hierarchical Attentive Network and BERT. 49–56. 14 indexed citations
6.
Barnes, Michael, Wendy Liu, Anindya Sarkar, et al.. (2017). Whole tumor section quantitative image analysis maximizes between-pathologists' reproducibility for clinical immunohistochemistry-based biomarkers. Laboratory Investigation. 97(12). 1508–1515. 17 indexed citations
7.
Nguyen, Kien, Anindya Sarkar, & Anil K. Jain. (2014). Prostate Cancer Grading: Use of Graph Cut and Spatial Arrangement of Nuclei. IEEE Transactions on Medical Imaging. 33(12). 2254–2270. 50 indexed citations
8.
9.
Kandanelli, Ramesh, Anindya Sarkar, & Uday Maitra. (2013). Tb3+ sensitization in a deoxycholate organogel matrix, and selective quenching of luminescence by an aromatic nitro derivative. Dalton Transactions. 42(43). 15381–15381. 16 indexed citations
10.
Nguyen, Kien, Anindya Sarkar, & Anil K. Jain. (2012). Structure and Context in Prostatic Gland Segmentation and Classification. Lecture notes in computer science. 15(Pt 1). 115–123. 62 indexed citations
11.
Nataraj, Lakshmanan, Anindya Sarkar, & B.S. Manjunath. (2010). Improving re-sampling detection by adding noise. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7541. 75410I–75410I. 16 indexed citations
12.
Sarkar, Anindya, Upamanyu Madhow, & B.S. Manjunath. (2010). Matrix Embedding With Pseudorandom Coefficient Selection and Error Correction for Robust and Secure Steganography. IEEE Transactions on Information Forensics and Security. 5(2). 225–239. 32 indexed citations
13.
Sarkar, Anindya, et al.. (2010). Efficient and Robust Detection of Duplicate Videos in a Large Database. IEEE Transactions on Circuits and Systems for Video Technology. 20(6). 870–885. 25 indexed citations
14.
Sarkar, Anindya, Lakshmanan Nataraj, & B.S. Manjunath. (2009). Detection of seam carving and localization of seam insertions in digital images. 107–116. 58 indexed citations
15.
Sarkar, Anindya, Kaushal Solanki, & B.S. Manjunath. (2008). Further study on YASS: steganography based on randomized embedding to resist blind steganalysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6819. 681917–681917. 41 indexed citations
16.
Sarkar, Anindya, et al.. (2008). Steganographic capacity estimation for the statistical restoration framework. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6819. 681916–681916.
17.
Gelasca, Elisa Drelie, et al.. (2007). UThe Vision Research Lab of UCSB at TRECVID 2007.. TRECVID. 1 indexed citations
18.
Kleban, Jim, et al.. (2007). Feature fusion and redundancy pruning for rush video summarization. 84–88. 13 indexed citations
19.
Sarkar, Anindya, Upamanyu Madhow, Shivkumar Chandrasekaran, & B.S. Manjunath. (2007). Adaptive MPEG-2 video data hiding scheme. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6505. 65051D–65051D. 11 indexed citations
20.
Sarkar, Anindya, et al.. (2007). <title>Video fingerprinting: features for duplicate and similar video detection and query-based video retrieval</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6820. 68200E–68200E. 19 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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