C. Chandra Sekhar

781 total citations
66 papers, 448 citations indexed

About

C. Chandra Sekhar is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, C. Chandra Sekhar has authored 66 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 41 papers in Signal Processing and 22 papers in Computer Vision and Pattern Recognition. Recurrent topics in C. Chandra Sekhar's work include Speech and Audio Processing (28 papers), Speech Recognition and Synthesis (23 papers) and Music and Audio Processing (14 papers). C. Chandra Sekhar is often cited by papers focused on Speech and Audio Processing (28 papers), Speech Recognition and Synthesis (23 papers) and Music and Audio Processing (14 papers). C. Chandra Sekhar collaborates with scholars based in India, Australia and Switzerland. C. Chandra Sekhar's co-authors include A. D. Dileep, B. Yegnanarayana, S. Chandrakala, V. Srinivasa Chakravarthy, Suryakanth V. Gangashetty, R. Anitha, Hema A. Murthy, Roya Rozati, Mehrtash Harandi and Srikanth Madikeri and has published in prestigious journals such as SHILAP Revista de lepidopterología, Fuzzy Sets and Systems and Applied Soft Computing.

In The Last Decade

C. Chandra Sekhar

61 papers receiving 418 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
C. Chandra Sekhar India	11	250	218	178	62	42	66	448
Mahdi Jampour Iran	10	78 0.3×	37 0.2×	245 1.4×	58 0.9×	51 1.2×	35	326
Zhaojie Luo Japan	10	187 0.7×	137 0.6×	95 0.5×	10 0.2×	86 2.0×	27	316
Mouldi Bedda Algeria	9	269 1.1×	127 0.6×	82 0.5×	28 0.5×	6 0.1×	44	388
Liang-Hua Chen Taiwan	11	87 0.3×	73 0.3×	363 2.0×	18 0.3×	8 0.2×	30	411
Joumana Ghosn Canada	7	87 0.3×	77 0.4×	222 1.2×	21 0.3×	5 0.1×	10	317
Pradip K. Das India	10	96 0.4×	85 0.4×	197 1.1×	82 1.3×	13 0.3×	61	326
Yogesh Kumar India	8	99 0.4×	29 0.1×	75 0.4×	19 0.3×	22 0.5×	37	274
Kiyoung Yang United States	7	138 0.6×	176 0.8×	64 0.4×	5 0.1×	5 0.1×	11	306
P. de Souza New Zealand	5	360 1.4×	267 1.2×	87 0.5×	4 0.1×	16 0.4×	9	460
Prasenjit Dey India	10	154 0.6×	77 0.4×	154 0.9×	64 1.0×	7 0.2×	25	362

Countries citing papers authored by C. Chandra Sekhar

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sekhar, C. Chandra, et al.. (2017). Distance metric learning-based kernel gram matrix learning for pattern analysis tasks in kernel feature space. Pattern Analysis and Applications. 21(3). 847–867. 2 indexed citations

Sekhar, C. Chandra, et al.. (2017). Distance Metric Learnt Kernel based SVMs for Semi-Supervised Pattern Classification. 1–6. 2 indexed citations

Dawalatabad, Nauman, Srikanth Madikeri, C. Chandra Sekhar, & Hema A. Murthy. (2016). Two-Pass IB Based Speaker Diarization System Using Meeting-Specific ANN Based Features. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2199–2203. 4 indexed citations

Sekhar, C. Chandra, et al.. (2015). Automatic Image Annotation Using Convex Deep Learning Models. 92–99. 1 indexed citations

Sekhar, C. Chandra, et al.. (2014). Prepartum and postpartum reproductive problems in bovines - a retrospective study of 711 cows.. Intas Polivet. 15(2). 199–204.

Sekhar, C. Chandra, et al.. (2014). Techniques for Improving the Performance of Image Retrieval using Relevance Feedback. 1–8. 1 indexed citations

Dileep, A. D., et al.. (2012). A Review of Kernel Methods Based Approaches to Classification and Clustering of Sequential Patterns, Part I. IGI Global eBooks. 251–278. 1 indexed citations

Sekhar, C. Chandra, et al.. (2012). Cholestrol Emboli Syndrome: Acute Renal Insufficiency After a Procedure or a Thrombolytic Therapy or Anticoagulant Therapy. Indian Journal of Surgery. 75(S1). 432–435. 2 indexed citations

Dileep, A. D., et al.. (2011). A Review of Kernel Methods Based Approaches to Classification and Clustering of Sequential Patterns, Part II. IGI Global eBooks. 51–71. 1 indexed citations

10.

Dileep, A. D., et al.. (2011). A Review of Kernel Methods Based Approaches to Classification and Clustering of Sequential Patterns, Part I. IGI Global eBooks. 24–50. 1 indexed citations

11.

Dileep, A. D. & C. Chandra Sekhar. (2009). Representation and feature selection using multiple kernel learning. 717–722. 18 indexed citations

12.

Rozati, Roya, et al.. (2008). Evaluation of the Phthalate Esters in South Indian Women with Endometriosis. SHILAP Revista de lepidopterología. 10 indexed citations

13.

Sekhar, C. Chandra, et al.. (2008). Large margin AR model for time series classification. Proceedings - International Conference on Pattern Recognition. 3. 1–4. 3 indexed citations

14.

Chakravarthy, V. Srinivasa, et al.. (2006). Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines. HAL (Le Centre pour la Communication Scientifique Directe). 62 indexed citations

15.

Gangashetty, Suryakanth V., C. Chandra Sekhar, & B. Yegnanarayana. (2005). Spotting consonant-vowel units in continuous speech using alitoassociative neural networks and support vector machines. 401–410. 4 indexed citations

16.

Sekhar, C. Chandra & Marimuthu Palaniswami. (2004). Classification of multidimensional trajectories for acoustic modeling using support vector machines. 4. 153–158. 1 indexed citations

17.

Gangashetty, Suryakanth V., et al.. (2004). Combining evidence from multiple modular networks for recognition of consonant-vowel units of speech. 1. 686–691. 2 indexed citations

18.

Sekhar, C. Chandra & B. Yegnanarayana. (2002). Classification of CV transitions in continuous speech using neural network models. 97–100. 1 indexed citations

19.

Gupta, Srikant, et al.. (1987). An acoustic-phonetic expert for analysis and processing of continuous speech in hindi. 1369–1372. 7 indexed citations

20.

Reddy, C. R. R. M., et al.. (1971). Relation of reverse smoking to carcinoma of the hard palate.. PubMed. 8(4). 263–8. 4 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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