Rakesh Mehta

2.3k total citations
11 papers, 510 citations indexed

About

Rakesh Mehta is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Computational Mechanics. According to data from OpenAlex, Rakesh Mehta has authored 11 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 2 papers in Biomedical Engineering and 1 paper in Computational Mechanics. Recurrent topics in Rakesh Mehta's work include Image Retrieval and Classification Techniques (6 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Medical Image Segmentation Techniques (3 papers). Rakesh Mehta is often cited by papers focused on Image Retrieval and Classification Techniques (6 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Medical Image Segmentation Techniques (3 papers). Rakesh Mehta collaborates with scholars based in Ireland, Finland and India. Rakesh Mehta's co-authors include Karen Egiazarian, Timo Kuula, Päivi Heikkilä, Susanna Aromaa, S Mach, Marja Liinasuo, Franziska Schmalfuß, Juhani Heilala, Eija Kaasinen and Menouer Boubekeur and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition and Pattern Recognition Letters.

In The Last Decade

Rakesh Mehta

11 papers receiving 479 citations

Peers

Rakesh Mehta

CVPR

IME

MT

BE

AI

Grahame Cooper United Kingdom

Maurice Pillet France

Sergey Ivanov Russia

Maryam Mousavi Malaysia

Nagul Cooharojananone Thailand

Arvind Kalia India

André F. Gygax Australia

Peng Pan China

Muhammad Zawish Ireland

Theam Foo Ng Malaysia

Grahame Cooper United Kingdom

Rakesh Mehta

22 ×0.1

CVPR

67 ×0.4

IME

18 ×0.3

MT

25 ×0.5

BE

85 ×1.8

AI

Citations per year, relative to Rakesh Mehta Rakesh Mehta (= 1×) peers Grahame Cooper

Countries citing papers authored by Rakesh Mehta

Since Specialization

Citations

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

Fields of papers citing papers by Rakesh Mehta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rakesh Mehta

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

All Works

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11 of 11 papers shown

1.

Kaasinen, Eija, Franziska Schmalfuß, Cemalettin Öztürk, et al.. (2019). Empowering and engaging industrial workers with Operator 4.0 solutions. Computers & Industrial Engineering. 139. 105678–105678. 205 indexed citations

2.

Ruiz, Idoia, Bogdan Raducanu, Rakesh Mehta, & Jaume Amores. (2019). Optimizing speed/accuracy trade-off for person re-identification via knowledge distillation. Engineering Applications of Artificial Intelligence. 87. 103309–103309. 13 indexed citations

3.

Mehta, Rakesh & Jaume Amores. (2018). Improving detection speed in video by exploiting frame correlation. Pattern Recognition Letters. 112. 303–309. 1 indexed citations

4.

Mehta, Rakesh & Karen Egiazarian. (2016). Rotation Invariant Texture Description Using Symmetric Dense Microblock Difference. IEEE Signal Processing Letters. 23(6). 833–837. 5 indexed citations

5.

Mehta, Rakesh & Karen Egiazarian. (2016). Texture Classification Using Dense Micro-Block Difference. IEEE Transactions on Image Processing. 25(4). 1604–1616. 39 indexed citations

6.

Mehta, Rakesh & Karen Egiazarian. (2015). Dominant Rotated Local Binary Patterns (DRLBP) for texture classification. Pattern Recognition Letters. 71. 16–22. 137 indexed citations

7.

Mehta, Rakesh & Karen Egiazarian. (2013). Rotated Local Binary Pattern (RLBP) - Rotation Invariant Texture Descriptor. 497–502. 28 indexed citations

8.

Mehta, Rakesh, Jirui Yuan, & Karen Egiazarian. (2013). Face recognition using scale-adaptive directional and textural features. Pattern Recognition. 47(5). 1846–1858. 37 indexed citations

9.

Mehta, Rakesh, Jirui Yuan, & Karen Egiazarian. (2011). Local polynomial approximation-local binary pattern (LPA-LBP) based face classification. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7881. 78810N–78810N. 3 indexed citations

10.

Mehta, Rakesh, et al.. (2007). FPGA based system for color space transformation RGB to YIQ and YCbCr. 1345–1349. 39 indexed citations

11.

Sweet, L. M., et al.. (1982). Software for Eight-Bit Microprocessors in Multivariable Digital Control Systems. Journal of Dynamic Systems Measurement and Control. 104(4). 305–310. 3 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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