Vijay Chandrasekhar

8.1k total citations · 1 hit paper
100 papers, 4.6k citations indexed

About

Vijay Chandrasekhar is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Vijay Chandrasekhar has authored 100 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Computer Vision and Pattern Recognition, 31 papers in Aerospace Engineering and 23 papers in Artificial Intelligence. Recurrent topics in Vijay Chandrasekhar's work include Advanced Image and Video Retrieval Techniques (61 papers), Image Retrieval and Classification Techniques (34 papers) and Robotics and Sensor-Based Localization (31 papers). Vijay Chandrasekhar is often cited by papers focused on Advanced Image and Video Retrieval Techniques (61 papers), Image Retrieval and Classification Techniques (34 papers) and Robotics and Sensor-Based Localization (31 papers). Vijay Chandrasekhar collaborates with scholars based in Singapore, United States and China. Vijay Chandrasekhar's co-authors include Bernd Girod, Gabriel Takacs, Sam S. Tsai, Radek Grzeszczuk, Winston K.G. Seah, Jie Lin, David Chen, Yoo Sang Choo, Andrew D. Bagdanov and Suman K. Ghosh and has published in prestigious journals such as IEEE Transactions on Image Processing, Joule and International Journal of Computer Vision.

In The Last Decade

Vijay Chandrasekhar

98 papers receiving 4.4k citations

Hit Papers

ICDAR 2015 competition on Robust Reading 2015 2026 2018 2022 2015 250 500 750
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. ICDAR 2015 competition on Robust Reading
    2015 874 citations Vijay Chandrasekhar et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vijay Chandrasekhar Singapore 33 3.2k 896 870 651 641 100 4.6k
Sen Wang China 34 1.3k 0.4× 1.5k 1.7× 606 0.7× 1.5k 2.3× 169 0.3× 167 4.1k
Lu Yu China 37 4.3k 1.3× 312 0.3× 408 0.5× 287 0.4× 945 1.5× 275 5.5k
Qinggang Meng United Kingdom 29 1.7k 0.5× 425 0.5× 583 0.7× 342 0.5× 361 0.6× 168 4.2k
Jürgen Beyerer Germany 27 1.9k 0.6× 565 0.6× 517 0.6× 240 0.4× 235 0.4× 420 3.5k
Fei Wu China 29 1.9k 0.6× 169 0.2× 972 1.1× 187 0.3× 496 0.8× 188 4.2k
Alireza Bab‐Hadiashar Australia 32 820 0.3× 572 0.6× 724 0.8× 470 0.7× 95 0.1× 171 3.1k
Zhi Liu China 36 1.1k 0.3× 869 1.0× 774 0.9× 2.4k 3.7× 184 0.3× 300 5.1k
Zheng Ma China 35 615 0.2× 1.2k 1.3× 512 0.6× 4.1k 6.3× 519 0.8× 252 5.9k
Jingjing Li China 38 3.0k 0.9× 130 0.1× 2.8k 3.2× 415 0.6× 221 0.3× 249 5.3k
Mu Zhou China 29 438 0.1× 906 1.0× 489 0.6× 1.9k 2.9× 62 0.1× 249 3.3k

Countries citing papers authored by Vijay Chandrasekhar

Since Specialization
Citations

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

Fields of papers citing papers by Vijay Chandrasekhar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vijay Chandrasekhar

This figure shows the co-authorship network connecting the top 25 collaborators of Vijay Chandrasekhar. A scholar is included among the top collaborators of Vijay Chandrasekhar 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 Vijay Chandrasekhar. Vijay Chandrasekhar 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.
Suganya, R., et al.. (2025). Wireless Sensor Networks in Environmental Monitoring Applications Challenges and Future Directions. ITM Web of Conferences. 76. 3002–3002.
2.
Foo, Chuan-Sheng, et al.. (2021). Classify and generate: Using classification latent space representations for image generations. Neurocomputing. 471. 296–334. 1 indexed citations
3.
Tan, Benjamin Hong Meng, et al.. (2021). DOReN: Toward Efficient Deep Convolutional Neural Networks with Fully Homomorphic Encryption. IEEE Transactions on Information Forensics and Security. 16. 3740–3752. 34 indexed citations
4.
Pham, Quang-Hieu, Ramanpreet Singh Pahwa, Yuda Chen, et al.. (2020). A*3D Dataset: Towards Autonomous Driving in Challenging Environments. 2267–2273. 108 indexed citations
5.
Dutta, Rahul, Salahuddin Raju, Yong‐Joon Jeon, et al.. (2019). Learning of Multi-Dimensional Analog Circuits Through Generative Adversarial Network (GAN). 394–399. 1 indexed citations
6.
Foo, Chuan-Sheng, et al.. (2019). TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. 1–6. 15 indexed citations
7.
Lin, Jie, et al.. (2019). EAST-DNN: Expediting architectural SimulaTions using deep neural networks. 1–2. 1 indexed citations
8.
Chen, Zhuo, et al.. (2019). Beyond Ranking Loss: Deep Holographic Networks for Multi-Label Video Search. DR-NTU (Nanyang Technological University). 879–883. 2 indexed citations
9.
Foo, Chuan-Sheng, et al.. (2018). The Unusual Effectiveness of Averaging in GAN Training. arXiv (Cornell University). 10 indexed citations
10.
Mertikopoulos, Panayotis, Houssam Zenati, Bruno Lecouat, et al.. (2018). Mirror descent in saddle-point problems: Going the extra (gradient) mile.. arXiv (Cornell University). 9 indexed citations
11.
Hippalgaonkar, Kedar, Jeroen van Duren, Shaffiq A. Jaffer, et al.. (2018). Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing. Joule. 2(8). 1410–1420. 256 indexed citations
12.
Mandal, Bappaditya, et al.. (2017). VC-I2R@ImageCLEF2017: Ensemble of Deep Learned Features for Lifelog Video Summarization. CLEF (Working Notes). 7 indexed citations
13.
Chandrasekhar, Vijay, et al.. (2016). Notice of Removal Co-sparsity regularized deep hashing for image instance retrieval. 2450–2454. 1 indexed citations
14.
Chandrasekhar, Vijay, et al.. (2016). A practical guide to CNNs and Fisher Vectors for image instance retrieval. Signal Processing. 128. 426–439. 55 indexed citations
15.
Duan, Ling‐Yu, Vijay Chandrasekhar, Jie Chen, et al.. (2015). Overview of the MPEG-CDVS Standard. IEEE Transactions on Image Processing. 25(1). 179–194. 100 indexed citations
16.
Chen, David, Sam S. Tsai, Vijay Chandrasekhar, et al.. (2011). Residual Enhanced Visual Vectors for on-device image matching. 850–854. 28 indexed citations
17.
Chandrasekhar, Vijay, Mehmet Emre Sargin, & David A. Ross. (2011). Automatic Language Identification in music videos with low level audio and visual features. 14 indexed citations
18.
Chandrasekhar, Vijay, Sam S. Tsai, Gabriel Takacs, et al.. (2010). Low latency image retrieval with progressive transmission of CHoG descriptors. 41–46. 21 indexed citations
19.
Chandrasekhar, Vijay, et al.. (2007). Experimental Analysis of Area Localization Scheme for Sensor Networks. National University of Singapore. 4013–4018. 5 indexed citations
20.
Chandrasekhar, Vijay & Winston K.G. Seah. (2006). An Area Localization Scheme for Underwater Sensor Networks. 1–8. 106 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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