S. Shivashankar

422 total citations
18 papers, 282 citations indexed

About

S. Shivashankar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, S. Shivashankar has authored 18 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Information Systems. Recurrent topics in S. Shivashankar's work include Image Retrieval and Classification Techniques (7 papers), Sentiment Analysis and Opinion Mining (4 papers) and Image Processing and 3D Reconstruction (4 papers). S. Shivashankar is often cited by papers focused on Image Retrieval and Classification Techniques (7 papers), Sentiment Analysis and Opinion Mining (4 papers) and Image Processing and 3D Reconstruction (4 papers). S. Shivashankar collaborates with scholars based in India and Sweden. S. Shivashankar's co-authors include P. S. Hiremath, Jagadeesh Pujari, P. S. Hiremath, Balaraman Ravindran, Sandeep Srivathsan, Ashish V. Tendulkar, K. Gayathri, Susan Elias and T. Srinivasan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Pattern Recognition Letters.

In The Last Decade

S. Shivashankar

18 papers receiving 241 citations

Peers

S. Shivashankar
S. Shivashankar
Citations per year, relative to S. Shivashankar S. Shivashankar (= 1×) peers K. Seetharaman

Countries citing papers authored by S. Shivashankar

Since Specialization
Citations

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

Fields of papers citing papers by S. Shivashankar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Shivashankar

This figure shows the co-authorship network connecting the top 25 collaborators of S. Shivashankar. A scholar is included among the top collaborators of S. Shivashankar 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. Shivashankar. S. Shivashankar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Shivashankar, S., et al.. (2018). Galois Field-based Approach for Rotation and Scale Invariant Texture Classification. International Journal of Image Graphics and Signal Processing. 10(9). 56–64. 5 indexed citations
2.
Shivashankar, S., et al.. (2017). Texture Representation Using Galois Field for Rotation Invariant Classification. 542. 237–240. 2 indexed citations
3.
Ravindran, Balaraman, et al.. (2015). CEIL: a scalable, resolution limit free approach for detecting communities in large networks. 2097–2103. 6 indexed citations
4.
Gayathri, K., Susan Elias, & S. Shivashankar. (2014). Composite Activity Recognition in Smart Homes Using Markov Logic Network. 24. 880–887. 7 indexed citations
5.
Shivashankar, S., Sandeep Srivathsan, Balaraman Ravindran, & Ashish V. Tendulkar. (2011). Multi-view methods for protein structure comparison using latent dirichlet allocation. Bioinformatics. 27(13). i61–i68. 20 indexed citations
6.
Shivashankar, S., et al.. (2010). Cluster Analysis of Customer Reviews Extracted from Web Pages. SHILAP Revista de lepidopterología. 5 indexed citations
7.
Hiremath, P. S., et al.. (2010). Script identification in a handwritten document image using texture features. 110–114. 26 indexed citations
8.
Hiremath, P. S., et al.. (2010). Writer identification in a handwritten document image using texture features. 7. 139–142. 8 indexed citations
9.
Hiremath, P. S., et al.. (2010). Conceptual level similarity measure based review spam detection. 416–423. 44 indexed citations
10.
Shivashankar, S., et al.. (2010). QUALITY ASSESSMENT OF CUSTOMER REVIEWS EXTRACTED FROM WEB PAGES : A REVIEW CLUSTERING APPROACH. 2 indexed citations
11.
Hiremath, P. S., et al.. (2009). Web based Quality Assessment of Customer Reviews using Quartile Measure. 5 indexed citations
12.
Hiremath, P. S. & S. Shivashankar. (2008). Wavelet based co-occurrence histogram features for texture classification with an application to script identification in a document image. Pattern Recognition Letters. 29(9). 1182–1189. 64 indexed citations
13.
Hiremath, P. S. & S. Shivashankar. (2006). Wavelet Features for Texture Classification and Their Use in Script Identification. 419–422. 2 indexed citations
14.
Hiremath, P. S. & S. Shivashankar. (2006). WAVELET BASED FEATURES FOR TEXTURE CLASSIFICATION. 28 indexed citations
15.
Hiremath, P. S. & S. Shivashankar. (2006). Texture classification based on the wavelet decomposed image. 2006. 522–525. 1 indexed citations
16.
17.
Shivashankar, S. & Jagadeesh Pujari. (2006). WAVELET BASED FEATURES FOR COLOR TEXTURE CLASSIFICATION WITH APPLICATION TO CBIR. 53 indexed citations
18.
Shivashankar, S., et al.. (1963). Equilibrium relative humidity (ERH) relationships of processed arecanut and whole dried ripe nuts.. CFTRI Institutional Repository. 3 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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