Vikas Singh

4.0k total citations
120 papers, 2.5k citations indexed

About

Vikas Singh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Vikas Singh has authored 120 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 38 papers in Artificial Intelligence and 31 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Vikas Singh's work include Medical Image Segmentation Techniques (24 papers), Advanced Neuroimaging Techniques and Applications (23 papers) and Functional Brain Connectivity Studies (14 papers). Vikas Singh is often cited by papers focused on Medical Image Segmentation Techniques (24 papers), Advanced Neuroimaging Techniques and Applications (23 papers) and Functional Brain Connectivity Studies (14 papers). Vikas Singh collaborates with scholars based in United States, India and United Kingdom. Vikas Singh's co-authors include Sterling C. Johnson, Lopamudra Mukherjee, Chris Hinrichs, Guofan Xu, Moo K. Chung, Yunyang Xiong, Vamsi Krishna Ithapu, Jiming Peng, Hyunwoo J. Kim and Charles R. Dyer and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and Neurology.

In The Last Decade

Vikas Singh

111 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vikas Singh United States 26 995 544 440 385 319 120 2.5k
Kim‐Han Thung United States 22 552 0.6× 597 1.1× 324 0.7× 344 0.9× 352 1.1× 57 1.9k
Minjeong Kim United States 30 717 0.7× 348 0.6× 621 1.4× 326 0.8× 605 1.9× 129 2.6k
Carlos G. Puntonet Spain 26 532 0.5× 475 0.9× 174 0.4× 200 0.5× 368 1.2× 109 2.1k
Kayhan Batmanghelich United States 18 1.4k 1.4× 425 0.8× 355 0.8× 254 0.7× 269 0.8× 59 2.4k
Heikki Huttunen Finland 20 589 0.6× 533 1.0× 145 0.3× 289 0.8× 217 0.7× 90 2.2k
Tong Tong China 20 1.6k 1.6× 560 1.0× 544 1.2× 308 0.8× 173 0.5× 101 2.7k
Liang Sun China 19 563 0.6× 675 1.2× 509 1.2× 126 0.3× 332 1.0× 90 1.8k
Hasan Demirel Cyprus 34 2.8k 2.8× 609 1.1× 397 0.9× 198 0.5× 177 0.6× 174 4.6k
Le An United States 24 945 0.9× 366 0.7× 421 1.0× 122 0.3× 190 0.6× 78 1.8k
Jesse S. Jin Australia 25 1.2k 1.2× 241 0.4× 189 0.4× 244 0.6× 279 0.9× 126 2.3k

Countries citing papers authored by Vikas Singh

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vikas Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Vikas Singh. A scholar is included among the top collaborators of Vikas Singh 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 Vikas Singh. Vikas Singh 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
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Singh, Vikas, et al.. (2024). Multiple factors influence skin cancer development: A comprehensive review. 5(2). 116–122. 1 indexed citations
4.
Chakraborty, Rudrasis, et al.. (2022). On the Versatile Uses of Partial Distance Correlation in Deep Learning. Lecture notes in computer science. 13686. 327–346. 9 indexed citations
5.
Xiong, Yunyang, Hanxiao Liu, Suyog Gupta, et al.. (2021). MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. 3824–3833. 97 indexed citations
6.
Xiong, Yunyang, et al.. (2019). Resource Constrained Neural Network Architecture Search.. arXiv (Cornell University). 2 indexed citations
7.
Fernandes, Arthur, Érika Ramos de Alvarenga, Tiago Luciano Passafaro, et al.. (2019). PSII-6 Deep Learning image segmentation for extraction of body measurements and prediction of body weight in Nile tilapia. Journal of Animal Science. 97(Supplement_3). 236–237.
8.
Patel, Jignesh M., et al.. (2018). A Natural Language Interface for Dissemination of Reproducible Biomedical Data Science. Lecture notes in computer science. 11073. 197–205. 3 indexed citations
9.
Adluru, Nagesh, et al.. (2018). Efficient Relative Attribute Learning Using Graph Neural Networks. Lecture notes in computer science. 11218. 575–590. 15 indexed citations
10.
Kim, Hyunwoo J., et al.. (2017). Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging. PubMed. 2017. 5777–5786. 18 indexed citations
11.
Kim, Hyunwoo J., Brandon M. Smith, Nagesh Adluru, et al.. (2016). Abundant Inverse Regression Using Sufficient Reduction and Its Applications. Lecture notes in computer science. 9907. 570–584. 1 indexed citations
12.
Plumb, Gregory, et al.. (2015). S n FFT: a Julia toolkit for Fourier analysis of functions over permutations. Journal of Machine Learning Research. 16(1). 3469–3473. 3 indexed citations
13.
Kim, Won Hwa, Nagesh Adluru, Moo K. Chung, et al.. (2015). Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer's disease. NeuroImage. 118. 103–117. 32 indexed citations
14.
Kim, Won Hwa, Vikas Singh, Moo K. Chung, et al.. (2014). Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness. NeuroImage. 93. 107–123. 20 indexed citations
15.
Kondor, Risi, et al.. (2014). Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision. Neural Information Processing Systems. 27. 541–549. 12 indexed citations
16.
Mukherjee, Lopamudra, Vikas Singh, & Jiming Peng. (2011). Scale invariant cosegmentation for image groups. PubMed. 1881–1888. 92 indexed citations
17.
Mukherjee, Lopamudra, Vikas Singh, Jiming Peng, & Chris Hinrichs. (2010). Learning kernels for variants of normalized cuts: Convex relaxations and applications. PubMed. 7. 3145–3152. 7 indexed citations
18.
Hinrichs, Chris, Vikas Singh, Guofan Xu, & Sterling C. Johnson. (2010). Predictive markers for AD in a multi-modality framework: An analysis of MCI progression in the ADNI population. NeuroImage. 55(2). 574–589. 304 indexed citations
19.
Hinrichs, Chris, Vikas Singh, Lopamudra Mukherjee, et al.. (2009). Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset. NeuroImage. 48(1). 138–149. 173 indexed citations
20.
Schäfer, Sebastian, et al.. (2009). Real-time endovascular guidewire position simulation using shortest path algorithms. International Journal of Computer Assisted Radiology and Surgery. 4(6). 597–608. 17 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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