C. Chandra Sekhar
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Experimental and Cognitive Psychology
- Co-authors
- A. D. DileepB. YegnanarayanaS. ChandrakalaV. Srinivasa ChakravarthySuryakanth V. GangashettyR. AnithaHema A. MurthyRoya Rozati
- Topics
- Speech and Audio Processing (28 papers)Speech Recognition and Synthesis (23 papers)Music and Audio Processing (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaFuzzy Sets and SystemsApplied Soft Computing
- Partner nations
- IndiaAustraliaSwitzerland
In The Last Decade
C. Chandra Sekhar
61 papers receiving 418 citations
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 250
- Signal Processing 218
- Computer Vision and Pattern Recognition 178
- Media Technology 62
- Experimental and Cognitive Psychology 42
Countries citing papers authored by C. Chandra Sekhar
This map shows the geographic impact of C. Chandra Sekhar'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 C. Chandra Sekhar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Chandra Sekhar more than expected).
Fields of papers citing papers by C. Chandra Sekhar
This network shows the impact of papers produced by C. Chandra Sekhar. 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 C. Chandra Sekhar. The network helps show where C. Chandra Sekhar may publish in the future.
Co-authorship network of co-authors of C. Chandra Sekhar
This figure shows the co-authorship network connecting the top 25 collaborators of C. Chandra Sekhar. A scholar is included among the top collaborators of C. Chandra Sekhar 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 C. Chandra Sekhar. C. Chandra Sekhar 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 | 4 | |
| 3 | 1 | |
| 4 | Prepartum and postpartum reproductive problems in bovines - a retrospective study of 711 cows. | 0 |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 18 | |
| 10 | 10 | |
| 11 | 3 | |
| 12 | Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines | 62 |
| 13 | 4 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 8 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 7 | |
| 20 | Relation of reverse smoking to carcinoma of the hard palate. | 4 |
About C. Chandra Sekhar
C. Chandra Sekhar is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 66 papers that have together received 448 indexed citations. Recurring topics across this work include Speech and Audio Processing (28 papers), Speech Recognition and Synthesis (23 papers) and Music and Audio Processing (14 papers). The work is most often cited by research in Signal Processing (218 citations), Computer Vision and Pattern Recognition (178 citations) and Artificial Intelligence (250 citations). C. Chandra Sekhar has collaborated with scholars based in India, Australia and Switzerland. Frequent co-authors include A. D. Dileep, B. Yegnanarayana, S. Chandrakala, V. Srinivasa Chakravarthy, Suryakanth V. Gangashetty, R. Anitha, Hema A. Murthy, Roya Rozati, Nauman Dawalatabad and Mehrtash Harandi. Their work appears in journals such as SHILAP Revista de lepidopterología, Fuzzy Sets and Systems and Applied Soft Computing.
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.