Rutuparna Panda

5.9k total citations
166 papers, 4.4k citations indexed

About

Rutuparna Panda is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Rutuparna Panda has authored 166 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Computer Vision and Pattern Recognition, 34 papers in Artificial Intelligence and 27 papers in Media Technology. Recurrent topics in Rutuparna Panda's work include Medical Image Segmentation Techniques (28 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Image and Signal Denoising Methods (19 papers). Rutuparna Panda is often cited by papers focused on Medical Image Segmentation Techniques (28 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Image and Signal Denoising Methods (19 papers). Rutuparna Panda collaborates with scholars based in India, United States and Russia. Rutuparna Panda's co-authors include Ajith Abraham, Sanjay Agrawal, P. S. Kashyap, Satyaranjan Behera, Manoj Kumar Naik, Manoj Tripathi, N. S. Raghuwanshi, Lingraj Dora, R. K. Srivastava and Pradeep Kumar Das and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Pollution and Journal of Hydrology.

In The Last Decade

Rutuparna Panda

154 papers receiving 4.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rutuparna Panda India 37 1.2k 964 912 716 708 166 4.4k
Xiaohui Yuan United States 36 1.9k 1.6× 246 0.3× 949 1.0× 215 0.3× 323 0.5× 225 5.5k
Saeid Homayouni Canada 33 421 0.4× 172 0.2× 465 0.5× 215 0.3× 397 0.6× 197 4.6k
Paheding Sidike United States 21 431 0.4× 72 0.1× 457 0.5× 494 0.7× 1.2k 1.7× 53 4.2k
Zhi Ding United States 53 454 0.4× 192 0.2× 1.9k 2.1× 217 0.3× 130 0.2× 577 11.6k
Gonzalo Pájares Spain 36 1.8k 1.5× 77 0.1× 859 0.9× 111 0.2× 2.1k 2.9× 134 6.0k
Xinghua Li China 38 1.2k 1.1× 120 0.1× 302 0.3× 125 0.2× 176 0.2× 171 5.0k
José M. Peña Spain 42 647 0.6× 180 0.2× 1.4k 1.5× 105 0.1× 2.7k 3.8× 163 7.4k
Minglun Gong Canada 36 2.6k 2.2× 96 0.1× 375 0.4× 107 0.1× 472 0.7× 615 5.9k
D.R. Wilson United States 23 544 0.5× 525 0.5× 1.6k 1.8× 116 0.2× 1.2k 1.7× 86 4.2k
Liqiang Zhang China 35 786 0.7× 67 0.1× 334 0.4× 144 0.2× 267 0.4× 289 4.7k

Countries citing papers authored by Rutuparna Panda

Since Specialization
Citations

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

Fields of papers citing papers by Rutuparna Panda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rutuparna Panda

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

All Works

20 of 20 papers shown
1.
Das, Pradeep Kumar, Adyasha Sahu, Sukadev Meher, Rutuparna Panda, & Ajith Abraham. (2025). Enhanced detection of acute leukemia: A hybrid machine learning framework with adaptive weight-optimized level set evolution. Engineering Applications of Artificial Intelligence. 161. 112244–112244.
2.
Panda, Rutuparna, et al.. (2024). Adaptive Spatially-Weighted Region-Based Active Contour. International Journal of Image and Graphics. 26(3).
3.
Sarma, Hiren Kumar Deva, et al.. (2023). D-t-SNE: Predicting heart disease based on hyper parameter tuned MLP. Biomedical Signal Processing and Control. 86. 105129–105129. 5 indexed citations
4.
5.
Das, Gautam, et al.. (2022). A Novel Non-Entropic Objective Function for Multilevel Optimal Threshold Selection Using Adaptive Equilibrium Optimizer. SHILAP Revista de lepidopterología. 1 indexed citations
6.
Dora, Lingraj, et al.. (2022). Data science methodologies in smart healthcare: a review. Health and Technology. 12(2). 329–344. 5 indexed citations
7.
Panda, Rutuparna, et al.. (2022). Slime Mould-Seagull Optimizer. 2022 IEEE 7th International conference for Convergence in Technology (I2CT). 1–7. 2 indexed citations
8.
Das, Pradeep Kumar, Sukadev Meher, Rutuparna Panda, & Ajith Abraham. (2021). An Efficient Blood-Cell Segmentation for the Detection of Hematological Disorders. IEEE Transactions on Cybernetics. 52(10). 10615–10626. 84 indexed citations
9.
Srivastava, R. K., Rutuparna Panda, & Arun Chakraborty. (2020). Quantification of nitrogen transformation and leaching response to agronomic management for maize crop under rainfed and irrigated condition. Environmental Pollution. 265(Pt A). 114866–114866. 16 indexed citations
10.
Das, Pradeep Kumar, Sukadev Meher, Rutuparna Panda, & Ajith Abraham. (2019). A Review of Automated Methods for the Detection of Sickle Cell Disease. IEEE Reviews in Biomedical Engineering. 13. 309–324. 64 indexed citations
11.
Agrawal, Sanjay, et al.. (2019). A novel region‐based multimodal image fusion technique using improved dictionary learning. International Journal of Imaging Systems and Technology. 30(3). 558–576. 1 indexed citations
12.
Panda, Rutuparna. (2017). Institutional credit and agricultural development in Odisha: analysis of recent trends.. 36(1). 17–32. 2 indexed citations
13.
Biswal, Trinath, et al.. (2017). Classification, Properties and Characterization of Fly Ash ICCL Chowdhar and RSP, CPP I. international journal of green and herbal chemistry. 6(4). 2 indexed citations
14.
Panigrahi, P., et al.. (2015). Response of rain-fed rice to supplemental irrigation with drip and surface irrigation methods in eastern India.. International journal of tropical agriculture. 33. 971–975. 5 indexed citations
15.
Panda, Rutuparna, et al.. (2013). Appraisal of the erosion status in the eastern coastal region of India. Indian Journal of Soil Conservation. 41(2). 121–126. 3 indexed citations
16.
Panda, Rutuparna, et al.. (2011). Managing terraced lowland and medium sloping land for sustainable agriculture: A study from the eastern ghat region of India. Irrigation and Drainage. 60(5). 694–702. 2 indexed citations
17.
Panda, Rutuparna, et al.. (2009). Use of probability Distribution models in Rainfall Analysis for Postmonsoon Crop Planning in Eastern ghat Region of Orissa. Indian Journal of Dryland Agricultural Research and Development. 24(1). 75–80. 2 indexed citations
18.
Panda, Rutuparna, et al.. (2009). Effect of Climate Change on the Yield of Winter Wheat in West Midnapore, India. The International Journal of Climate Change Impacts and Responses. 1(1). 31–46. 1 indexed citations
19.
Behera, Satyaranjan & Rutuparna Panda. (2009). Effect of fertilization and irrigation schedule on water and fertilizer solute transport for wheat crop in a sub-humid sub-tropical region. Agriculture Ecosystems & Environment. 130(3-4). 141–155. 53 indexed citations
20.
Panda, Rutuparna & A. K. Bhattacharya. (1983). Lining of Small Irrigation Channels. Water and Energy International. 40(4). 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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