V. Chandrasekaran

421 citations
20 papers · 163 indexed · h-index 7
Topics
Retinal Imaging and Analysis (7 papers)Advanced Image Processing Techniques (5 papers)Glaucoma and retinal disorders (5 papers)
Journals
SHILAP Revista de lepidopterologíaMachine Vision and ApplicationsPattern Analysis and Applications

In The Last Decade

V. Chandrasekaran

19 papers receiving 147 citations

Peers

V. Chandrasekaran
Comparison fields: 5 of 31
  • Computer Vision and Pattern Recognition 111
  • Radiology, Nuclear Medicine and Imaging 80
  • Ophthalmology 64
  • Artificial Intelligence 21
  • Computational Theory and Mathematics 17
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Michel Cozic France
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V. Chandrasekaran relative to Michel Cozic France Michel Cozic's profile →
Citations per field
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Citations per year

Countries citing papers authored by V. Chandrasekaran

Since Specialization
Citations

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

Fields of papers citing papers by V. Chandrasekaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Chandrasekaran

This figure shows the co-authorship network connecting the top 25 collaborators of V. Chandrasekaran. A scholar is included among the top collaborators of V. Chandrasekaran 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 V. Chandrasekaran. V. Chandrasekaran 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
#WorkIndexed citations
1 3
2 1
3 1
4 1
5 5
6 18
7
FIELA: A Fast Image Encryption with Lorenz Attractor using Hybrid Computing
1
8 2
9 4
10 17
11 27
12 0
13 8
14 9
15
Automatic Detection of Anatomical Structures in Digital Fundus Retinal Images
39
16
Localization of Optic Disk Using Independent Component Analysis and Modified Structural Similarity Measure
3
17
A Fractional Derivative Approach for Robust Segmentation of Blood Vessels in Digital Fundus Retinal Images
1
18 16
19 4
20 3

About V. Chandrasekaran

V. Chandrasekaran is a scholar working on Computer Vision and Pattern Recognition, Ophthalmology and Media Technology, having authored 20 papers that have together received 163 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (7 papers), Advanced Image Processing Techniques (5 papers) and Glaucoma and retinal disorders (5 papers). The work is most often cited by research in Ophthalmology (64 citations), Computer Vision and Pattern Recognition (111 citations) and Radiology, Nuclear Medicine and Imaging (80 citations). V. Chandrasekaran has collaborated with scholars based in India, Australia and United States. Frequent co-authors include S. Balasubramanian, Swastik Pradhan, Marimuthu Palaniswami, Terry Caelli, Ravi Mukkamala, Pallav Kumar Baruah and A. Srinivasan. Their work appears in journals such as SHILAP Revista de lepidopterología, Machine Vision and Applications and Pattern Analysis and Applications.

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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