Rajib Kumar Jha

547 total citations
14 papers, 452 citations indexed

About

Rajib Kumar Jha is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Molecular Biology. According to data from OpenAlex, Rajib Kumar Jha has authored 14 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Statistical and Nonlinear Physics and 3 papers in Molecular Biology. Recurrent topics in Rajib Kumar Jha's work include stochastic dynamics and bifurcation (7 papers), Advanced Steganography and Watermarking Techniques (7 papers) and Digital Media Forensic Detection (6 papers). Rajib Kumar Jha is often cited by papers focused on stochastic dynamics and bifurcation (7 papers), Advanced Steganography and Watermarking Techniques (7 papers) and Digital Media Forensic Detection (6 papers). Rajib Kumar Jha collaborates with scholars based in India. Rajib Kumar Jha's co-authors include Vivek Singh Verma, Rajlaxmi Chouhan, Aparajita Ojha, Prabir Kumar Biswas, Anuj Bhardwaj, Subrata Kumar Ghosh, T.V.K. Gupta and Milind M. Mushrif and has published in prestigious journals such as Expert Systems with Applications, Journal of the Franklin Institute and Multimedia Tools and Applications.

In The Last Decade

Rajib Kumar Jha

14 papers receiving 426 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rajib Kumar Jha India 10 382 74 67 30 23 14 452
Rajlaxmi Chouhan India 11 203 0.5× 70 0.9× 106 1.6× 9 0.3× 12 0.5× 34 334
Aihua Zhang China 10 109 0.3× 41 0.6× 57 0.9× 17 0.6× 20 0.9× 37 310
Jean-Pierre Drouhard Canada 8 130 0.3× 44 0.6× 53 0.8× 19 0.6× 48 2.1× 11 383
Longhao Yuan Japan 9 215 0.6× 81 1.1× 21 0.3× 25 0.8× 45 2.0× 14 461
Daniyar Turmukhambetov United Kingdom 6 237 0.6× 36 0.5× 13 0.2× 9 0.3× 98 4.3× 10 362
Yuanyuan Shang China 12 388 1.0× 60 0.8× 8 0.1× 48 1.6× 58 2.5× 47 503
Bahjat Kawar Israel 3 333 0.9× 43 0.6× 11 0.2× 16 0.5× 77 3.3× 5 431
Boyán Bonev Spain 9 143 0.4× 26 0.4× 11 0.2× 18 0.6× 111 4.8× 19 253
Jean‐Philippe Domenger France 10 162 0.4× 17 0.2× 9 0.1× 12 0.4× 39 1.7× 34 279
Shiran Zada United States 4 394 1.0× 23 0.3× 10 0.1× 27 0.9× 92 4.0× 8 524

Countries citing papers authored by Rajib Kumar Jha

Since Specialization
Citations

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

Fields of papers citing papers by Rajib Kumar Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajib Kumar Jha. 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 Rajib Kumar Jha. The network helps show where Rajib Kumar Jha may publish in the future.

Co-authorship network of co-authors of Rajib Kumar Jha

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

All Works

14 of 14 papers shown
1.
Gupta, T.V.K., et al.. (2020). Wear analysis of abrasive waterjet nozzle using suprathreshold stochastic resonance technique. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 235(2). 499–504. 2 indexed citations
2.
Verma, Vivek Singh, Anuj Bhardwaj, & Rajib Kumar Jha. (2019). A new scheme for watermark extraction using combined noise-induced resonance and support vector machine with PCA based feature reduction. Multimedia Tools and Applications. 78(16). 23203–23224. 14 indexed citations
3.
Verma, Vivek Singh & Rajib Kumar Jha. (2017). LWT–DSR based new robust framework for watermark extraction under intentional attack conditions. Journal of the Franklin Institute. 354(14). 6422–6449. 11 indexed citations
4.
Bhardwaj, Anuj, Vivek Singh Verma, & Rajib Kumar Jha. (2017). Robust video watermarking using significant frame selection based on coefficient difference of lifting wavelet transform. Multimedia Tools and Applications. 77(15). 19659–19678. 41 indexed citations
5.
Verma, Vivek Singh, et al.. (2016). Robust image watermarking using combined DSR-SVM with PCA based feature reduction. 42. 323–327. 1 indexed citations
6.
Verma, Vivek Singh & Rajib Kumar Jha. (2015). An Overview of Robust Digital Image Watermarking. IETE Technical Review. 32(6). 479–496. 46 indexed citations
7.
Verma, Vivek Singh, Rajib Kumar Jha, & Aparajita Ojha. (2015). Digital watermark extraction using support vector machine with principal component analysis based feature reduction. Journal of Visual Communication and Image Representation. 31. 75–85. 50 indexed citations
8.
Verma, Vivek Singh, Rajib Kumar Jha, & Aparajita Ojha. (2015). Significant region based robust watermarking scheme in lifting wavelet transform domain. Expert Systems with Applications. 42(21). 8184–8197. 95 indexed citations
9.
Verma, Vivek Singh & Rajib Kumar Jha. (2014). Improved watermarking technique based on significant difference of lifting wavelet coefficients. Signal Image and Video Processing. 9(6). 1443–1450. 51 indexed citations
10.
Chouhan, Rajlaxmi, Rajib Kumar Jha, & Prabir Kumar Biswas. (2013). Enhancement of dark and low‐contrast images using dynamic stochastic resonance. IET Image Processing. 7(2). 174–184. 74 indexed citations
11.
Jha, Rajib Kumar & Rajlaxmi Chouhan. (2012). Noise-induced contrast enhancement using stochastic resonance on singular values. Signal Image and Video Processing. 8(2). 339–347. 45 indexed citations
12.
Jha, Rajib Kumar, et al.. (2012). Dynamic stochastic resonance-based improved watermark extraction in DWT-SVD domain. 632–636. 2 indexed citations
13.
Jha, Rajib Kumar, Rajlaxmi Chouhan, & Prabir Kumar Biswas. (2012). Noise-induced contrast enhancement of dark images using non-dynamic stochastic resonance. 1–5. 19 indexed citations
14.
Jha, Rajib Kumar, et al.. (2012). Dynamic stochastic resonance-based improved watermark extraction from audio signal. 11. 1–5. 1 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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