Krishna Gopal Dhal

2.3k total citations
81 papers, 1.5k citations indexed

About

Krishna Gopal Dhal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Krishna Gopal Dhal has authored 81 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Vision and Pattern Recognition, 40 papers in Artificial Intelligence and 19 papers in Media Technology. Recurrent topics in Krishna Gopal Dhal's work include Metaheuristic Optimization Algorithms Research (29 papers), Image Enhancement Techniques (20 papers) and Advanced Image and Video Retrieval Techniques (11 papers). Krishna Gopal Dhal is often cited by papers focused on Metaheuristic Optimization Algorithms Research (29 papers), Image Enhancement Techniques (20 papers) and Advanced Image and Video Retrieval Techniques (11 papers). Krishna Gopal Dhal collaborates with scholars based in India, Mexico and Jordan. Krishna Gopal Dhal's co-authors include Sanjoy Das, Swarnajit Ray, Arunita Das, Jorge Gálvez, Arunita Das, Rebika Rai, Abdelazim G. Hussien, Prabir Kumar Naskar, Amit Shiuly and Erik Cuevas and has published in prestigious journals such as Scientific Reports, Construction and Building Materials and Neurocomputing.

In The Last Decade

Krishna Gopal Dhal

79 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Krishna Gopal Dhal India 22 726 673 241 144 111 81 1.5k
Mukesh Saraswat India 21 746 1.0× 948 1.4× 238 1.0× 134 0.9× 83 0.7× 66 1.8k
Jorge Gálvez Mexico 17 374 0.5× 474 0.7× 145 0.6× 156 1.1× 60 0.5× 46 992
Heming Jia China 22 604 0.8× 952 1.4× 216 0.9× 331 2.3× 35 0.3× 57 1.7k
Eva Tuba Serbia 26 500 0.7× 796 1.2× 104 0.4× 102 0.7× 68 0.6× 76 1.7k
Sanjoy Das India 18 462 0.6× 312 0.5× 210 0.9× 68 0.5× 47 0.4× 58 947
Swarnajit Ray India 16 380 0.5× 388 0.6× 124 0.5× 78 0.5× 49 0.4× 27 752
Suk‐Hwan Lee South Korea 18 871 1.2× 385 0.6× 74 0.3× 74 0.5× 49 0.4× 188 1.4k
Zhi Tang China 21 1.6k 2.2× 604 0.9× 267 1.1× 196 1.4× 33 0.3× 131 2.1k
Hao Gao China 18 613 0.8× 503 0.7× 153 0.6× 151 1.0× 20 0.2× 116 1.4k
Xiao Chen China 20 458 0.6× 443 0.7× 99 0.4× 184 1.3× 52 0.5× 130 2.1k

Countries citing papers authored by Krishna Gopal Dhal

Since Specialization
Citations

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

Fields of papers citing papers by Krishna Gopal Dhal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Krishna Gopal Dhal. 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 Krishna Gopal Dhal. The network helps show where Krishna Gopal Dhal may publish in the future.

Co-authorship network of co-authors of Krishna Gopal Dhal

This figure shows the co-authorship network connecting the top 25 collaborators of Krishna Gopal Dhal. A scholar is included among the top collaborators of Krishna Gopal Dhal 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 Krishna Gopal Dhal. Krishna Gopal Dhal 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, Arunita, et al.. (2025). Artificial hummingbird algorithm: Theory, variants, analysis, applications, and performance evaluation. Computer Science Review. 56. 100727–100727. 3 indexed citations
2.
Das, Arunita, et al.. (2024). Particle Swarm Optimizer Variants for Multi-level Thresholding: Theory, Performance Enhancement and Evaluation. Archives of Computational Methods in Engineering. 31(5). 3115–3150. 7 indexed citations
3.
Houssein, Essam H., Marwa M. Emam, Waleed Alomoush, et al.. (2024). An efficient improved parrot optimizer for bladder cancer classification. Computers in Biology and Medicine. 181. 109080–109080. 5 indexed citations
4.
Dhal, Krishna Gopal, et al.. (2024). A CNN-based model to count the leaves of rosette plants (LC-Net). Scientific Reports. 14(1). 1496–1496. 5 indexed citations
5.
Das, Arunita, et al.. (2023). Aquila-particle swarm based cooperative search optimizer with superpixel techniques for epithelial layer segmentation. Applied Soft Computing. 149. 110947–110947. 5 indexed citations
6.
Rai, Rebika, Krishna Gopal Dhal, Arunita Das, & Swarnajit Ray. (2023). An Inclusive Survey on Marine Predators Algorithm: Variants and Applications. Archives of Computational Methods in Engineering. 30(5). 3133–3172. 30 indexed citations
7.
8.
Dhal, Krishna Gopal, et al.. (2023). A Comprehensive Survey on Arithmetic Optimization Algorithm. Archives of Computational Methods in Engineering. 30(5). 3379–3404. 45 indexed citations
9.
Hussien, Abdelazim G., et al.. (2023). Reptile Search Algorithm: Theory, Variants, Applications, and Performance Evaluation. Archives of Computational Methods in Engineering. 31(1). 521–549. 28 indexed citations
10.
Dhal, Krishna Gopal, Swarnajit Ray, Rebika Rai, & Arunita Das. (2023). Archimedes Optimizer: Theory, Analysis, Improvements, and Applications. Archives of Computational Methods in Engineering. 30(4). 2543–2578. 19 indexed citations
11.
Hussien, Abdelazim G., et al.. (2023). A Comprehensive Survey on Aquila Optimizer. Archives of Computational Methods in Engineering. 30(7). 4449–4476. 46 indexed citations
12.
Das, Arunita, et al.. (2023). Information Added U-Net with Sharp Block for Nucleus Segmentation of Histopathology Images. Optical Memory and Neural Networks. 32(4). 318–330. 2 indexed citations
13.
Dhal, Krishna Gopal, et al.. (2023). Chaotic fitness-dependent quasi-reflected Aquila optimizer for superpixel based white blood cell segmentation. Neural Computing and Applications. 35(21). 15315–15332. 13 indexed citations
14.
Dhal, Krishna Gopal, et al.. (2023). A survey on the utilization of Superpixel image for clustering based image segmentation. Multimedia Tools and Applications. 82(23). 35493–35555. 23 indexed citations
15.
Dhal, Krishna Gopal, et al.. (2023). Illumination-Free Clustering Using Improved Slime Mould Algorithm for Acute Lymphoblastic Leukemia Image Segmentation. Journal of Bionic Engineering. 20(6). 2916–2934. 6 indexed citations
16.
Rai, Rebika, Arunita Das, & Krishna Gopal Dhal. (2022). Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review. Evolving Systems. 13(6). 889–945. 46 indexed citations
17.
Rai, Rebika, Arunita Das, Swarnajit Ray, & Krishna Gopal Dhal. (2022). Human-Inspired Optimization Algorithms: Theoretical Foundations, Algorithms, Open-Research Issues and Application for Multi-Level Thresholding. Archives of Computational Methods in Engineering. 29(7). 5313–5352. 30 indexed citations
18.
Dhal, Krishna Gopal, Swarnajit Ray, Arunita Das, & Sanjoy Das. (2018). A Survey on Nature-Inspired Optimization Algorithms and Their Application in Image Enhancement Domain. Archives of Computational Methods in Engineering. 26(5). 1607–1638. 88 indexed citations
19.
Dhal, Krishna Gopal, et al.. (2015). A Chaotic Lévy flight Approach in Bat and Firefly Algorithm for Gray level image Enhancement. International Journal of Image Graphics and Signal Processing. 7(7). 69–76. 14 indexed citations
20.
Dhal, Krishna Gopal, et al.. (2012). A novel human hand finger gesture recognition using machine learning. 882–887. 2 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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