S. Domnic
- Computer Vision and Pattern Recognition top 5%
- Plant Science
- Signal Processing top 10%
- Artificial Intelligence
- Ecology
- Co-authors
- G. G. Lakshmi PriyaRashmi S. NairK. SomasundaramAnil KumarRohit AgrawalByoung–Kwan ChoB. JanetMohammad Akbar Faqeerzada
- Topics
- Algorithms and Data Compression (11 papers)Video Analysis and Summarization (10 papers)Video Coding and Compression Technologies (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Image ProcessingFrontiers in Plant Science
- Partner nations
- IndiaSouth KoreaSingapore
In The Last Decade
S. Domnic
55 papers receiving 479 citations
Peers
Comparison fields: 5 of 92
- Computer Vision and Pattern Recognition 234
- Plant Science 123
- Signal Processing 99
- Artificial Intelligence 82
- Ecology 63
Countries citing papers authored by S. Domnic
This map shows the geographic impact of S. Domnic'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 S. Domnic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Domnic more than expected).
Fields of papers citing papers by S. Domnic
This network shows the impact of papers produced by S. Domnic. 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 S. Domnic. The network helps show where S. Domnic may publish in the future.
Co-authorship network of co-authors of S. Domnic
This figure shows the co-authorship network connecting the top 25 collaborators of S. Domnic. A scholar is included among the top collaborators of S. Domnic 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 S. Domnic. S. Domnic is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 1 | |
| 6 | 17 | |
| 7 | 10 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | Image Based Plant Phenotyping using Graph Based Method and Circular Hough Transform. | 2 |
| 15 | 3 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | Inverted index compression using Extended Golomb Code | 2 |
| 19 | 2 | |
| 20 | 2 |
About S. Domnic
S. Domnic is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 59 papers that have together received 509 indexed citations. Recurring topics across this work include Algorithms and Data Compression (11 papers), Video Analysis and Summarization (10 papers) and Video Coding and Compression Technologies (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (234 citations), Signal Processing (99 citations) and Analytical Chemistry (44 citations). S. Domnic has collaborated with scholars based in India, South Korea and Singapore. Frequent co-authors include G. G. Lakshmi Priya, Rashmi S. Nair, K. Somasundaram, Anil Kumar, Rohit Agrawal, Byoung–Kwan Cho, B. Janet, Mohammad Akbar Faqeerzada, Yun‐Soo Kim and Eunsoo Park. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Frontiers in Plant Science.
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.