Dilip K. Prasad

3.3k citations
110 papers · 2.0k indexed · 1 hit paper · h-index 22
Topics
Image and Object Detection Techniques (17 papers)Image Processing Techniques and Applications (13 papers)Robotics and Sensor-Based Localization (9 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsIEEE Transactions on Image Processing
Partner nations
SingaporeNorwayIndia

In The Last Decade

Dilip K. Prasad

102 papers receiving 1.9k citations

Hit Papers

Video Processing From Electro-Optical Sensors for Object ...20172026202020232017100200300

Peers

Dilip K. Prasad
Comparison fields: 5 of 143
  • Computer Vision and Pattern Recognition 959
  • Aerospace Engineering 365
  • Ocean Engineering 269
  • Media Technology 262
  • Artificial Intelligence 254
Replace Mark J. Burge with:
Mark J. Burge United States
Feng Lin China
Alexander A. Alemi United States
Camille Couprie France
Micael S. Couceiro Portugal
Deepu Rajan Singapore
Uvais Qidwai Qatar
Lu Fang China
Wilhelm Burger United States
Jie Li China
Dilip K. Prasad relative to Mark J. Burge United States Mark J. Burge's profile →
Citations per field
00.5×3.5×
Mark J. Burge · 1×
Citations per year

Countries citing papers authored by Dilip K. Prasad

Since Specialization
Citations

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

Fields of papers citing papers by Dilip K. Prasad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dilip K. Prasad. 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 Dilip K. Prasad. The network helps show where Dilip K. Prasad may publish in the future.

Co-authorship network of co-authors of Dilip K. Prasad

This figure shows the co-authorship network connecting the top 25 collaborators of Dilip K. Prasad. A scholar is included among the top collaborators of Dilip K. Prasad 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 Dilip K. Prasad. Dilip K. Prasad 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
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5 12
6 9
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11 20
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Fast segmentation of sub-cellular organelles
3

About Dilip K. Prasad

Dilip K. Prasad is a scholar working on Computer Vision and Pattern Recognition, Structural Biology and Media Technology, having authored 110 papers that have together received 2.0k indexed citations. Recurring topics across this work include Image and Object Detection Techniques (17 papers), Image Processing Techniques and Applications (13 papers) and Robotics and Sensor-Based Localization (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (959 citations), Media Technology (262 citations) and Ocean Engineering (269 citations). Dilip K. Prasad has collaborated with scholars based in Singapore, Norway and India. Frequent co-authors include Chai Quek, M.K.H. Leung, Deepu Rajan, Eshan Rajabally, Lily Rachmawati, Michael S. Brown, Dongliang Cheng, Siu‐Yeung Cho, Huixu Dong and I‐Ming Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.

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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