Hanuman Verma

523 total citations
13 papers, 426 citations indexed

About

Hanuman Verma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Hanuman Verma has authored 13 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 4 papers in Media Technology. Recurrent topics in Hanuman Verma's work include Medical Image Segmentation Techniques (6 papers), Multi-Criteria Decision Making (4 papers) and Brain Tumor Detection and Classification (4 papers). Hanuman Verma is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Multi-Criteria Decision Making (4 papers) and Brain Tumor Detection and Classification (4 papers). Hanuman Verma collaborates with scholars based in India, United Kingdom and Australia. Hanuman Verma's co-authors include R. K. Agrawal, Aditi Sharan, Dhirendra Kumar, Akshansh Gupta, Aparna Mehra, Naveen Kumar, Mukesh Prasad, Javier Andreu-Pérez, M. Tanveer and Chin‐Teng Lin and has published in prestigious journals such as Expert Systems with Applications, Applied Soft Computing and Pattern Recognition Letters.

In The Last Decade

Hanuman Verma

10 papers receiving 406 citations

Peers

Hanuman Verma

CVPR

AI

MT

NEURO

MSOR

Arvind Dhaka India

S. Ramathilagam India

Milind M. Mushrif India

Liping Zhao China

Mohammed A. Shehab Jordan

A. Vadivel India

G. Jothi India

Salima Ouadfel Algeria

Badal Soni India

Jia Wei China

Arvind Dhaka India

Hanuman Verma

169 ×0.8

CVPR

89 ×0.5

AI

38 ×0.4

MT

118 ×1.8

NEURO

26 ×0.5

MSOR

Citations per year, relative to Hanuman Verma Hanuman Verma (= 1×) peers Arvind Dhaka

Countries citing papers authored by Hanuman Verma

Since Specialization

Citations

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

Fields of papers citing papers by Hanuman Verma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanuman Verma

This figure shows the co-authorship network connecting the top 25 collaborators of Hanuman Verma. A scholar is included among the top collaborators of Hanuman Verma 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 Hanuman Verma. Hanuman Verma 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:

13 of 13 papers shown

1.

Verma, Hanuman, et al.. (2024). A hybrid approach for MRI brain image segmentation using KIFECM-IPSO algorithm. Expert Systems with Applications. 268. 126239–126239.

2.

Verma, Hanuman, et al.. (2022). Temporal deep learning architecture for prediction of COVID-19 cases in India. Expert Systems with Applications. 195. 116611–116611. 40 indexed citations

3.

Gupta, Akshansh, Dhirendra Kumar, Hanuman Verma, et al.. (2022). Recognition of multi-cognitive tasks from EEG signals using EMD methods. Neural Computing and Applications. 35(31). 22989–23006. 14 indexed citations

4.

Verma, Hanuman, et al.. (2020). A population based hybrid FCM-PSO algorithm for clustering analysis and segmentation of brain image. Expert Systems with Applications. 167. 114121–114121. 62 indexed citations

5.

Kumar, Dhirendra, R. K. Agrawal, & Hanuman Verma. (2019). Kernel intuitionistic fuzzy entropy clustering for MRI image segmentation. Soft Computing. 24(6). 4003–4026. 43 indexed citations

6.

Verma, Hanuman, Akshansh Gupta, & Dhirendra Kumar. (2019). A modified intuitionistic fuzzy c-means algorithm incorporating hesitation degree. Pattern Recognition Letters. 122. 45–52. 42 indexed citations

7.

Kumar, Dhirendra, Hanuman Verma, Aparna Mehra, & R. K. Agrawal. (2018). A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image. Multimedia Tools and Applications. 78(10). 12663–12687. 46 indexed citations

8.

Verma, Hanuman, et al.. (2018). Blood Vessel Segmentation for IRIS in Unconstrained Environments using Moment Method. International Journal of Computer Science and Engineering. 5(8). 8–14.

9.

Verma, Hanuman, R. K. Agrawal, & Aditi Sharan. (2015). An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation. Applied Soft Computing. 46. 543–557. 143 indexed citations

10.

Verma, Hanuman & R. K. Agrawal. (2015). Possibilistic Intuitionistic Fuzzy c-Means Clustering Algorithm for MRI Brain Image Segmentation. International Journal of Artificial Intelligence Tools. 24(5). 1550016–1550016. 15 indexed citations

11.

Verma, Hanuman, R. K. Agrawal, & Naveen Kumar. (2014). Improved fuzzy entropy clustering algorithm for MRI brain image segmentation. International Journal of Imaging Systems and Technology. 24(4). 277–283. 18 indexed citations

12.

Verma, Hanuman, et al.. (2012). An Image Matching Approach based on String Matching using Remainder-Prime Method. International Journal of Computer Applications. 56(8). 1–5. 1 indexed citations

13.

Verma, Hanuman & R. K. Agrawal. (2011). Automatic Segmentation of MRI Brain Image using Type-3 Fuzzy C-Means Clustering Algorithm.. Indian International Conference on Artificial Intelligence. 1060–1069. 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.

Explore authors with similar magnitude of impact