Munish Khanna

1.4k total citations
42 papers, 905 citations indexed

About

Munish Khanna is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Munish Khanna has authored 42 papers receiving a total of 905 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Ophthalmology and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Munish Khanna's work include Retinal Imaging and Analysis (18 papers), Glaucoma and retinal disorders (14 papers) and Retinal Diseases and Treatments (9 papers). Munish Khanna is often cited by papers focused on Retinal Imaging and Analysis (18 papers), Glaucoma and retinal disorders (14 papers) and Retinal Diseases and Treatments (9 papers). Munish Khanna collaborates with scholars based in India. Munish Khanna's co-authors include Law Kumar Singh, Rekha Singh, Shankar Thawkar, Hitendra Garg, Pooja Sharma, Satish J. Sharma, Robin Singh Bhadoria, Dilip Kumar Sharma, Naresh Chauhan and Himanshu Monga and has published in prestigious journals such as Measurement, Computers in Biology and Medicine and Heliyon.

In The Last Decade

Munish Khanna

41 papers receiving 866 citations

Peers

Munish Khanna

RNMI

CVPR

OPHTH

HIM

Law Kumar Singh India

Shankar Thawkar India

Tahira Nazir Pakistan

J. Dinesh Peter India

S. Sowmya Kamath India

Eugenio Vocaturo Italy

Samir Elmougy Egypt

Eswaran Perumal India

Shyr-Shen Yu Taiwan

Che‐Lun Hung Taiwan

Law Kumar Singh India

Munish Khanna

457 ×1.1

RNMI

303 ×1.0

296 ×1.1

CVPR

241 ×1.1

OPHTH

101 ×1.1

HIM

Citations per year, relative to Munish Khanna Munish Khanna (= 1×) peers Law Kumar Singh

Countries citing papers authored by Munish Khanna

Since Specialization

Citations

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

Fields of papers citing papers by Munish Khanna

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Munish Khanna

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

All Works

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20 of 20 papers shown

Singh, Law Kumar, Munish Khanna, & Rekha Singh. (2024). An enhanced soft-computing based strategy for efficient feature selection for timely breast cancer prediction: Wisconsin Diagnostic Breast Cancer dataset case. Multimedia Tools and Applications. 83(31). 76607–76672. 23 indexed citations

Singh, Law Kumar, Munish Khanna, & Rekha Singh. (2024). Feature subset selection through nature inspired computing for efficient glaucoma classification from fundus images. Multimedia Tools and Applications. 83(32). 77873–77944. 21 indexed citations

Khanna, Munish, et al.. (2024). An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study. Heliyon. 10(5). e26799–e26799. 30 indexed citations

Singh, Law Kumar, et al.. (2024). Correction to: Features fusion based novel approach for efficient blood vessel segmentation from fundus images. Multimedia Tools and Applications. 83(28). 72175–72175. 2 indexed citations

Singh, Law Kumar, Munish Khanna, Hitendra Garg, & Rekha Singh. (2023). Emperor penguin optimization algorithm- and bacterial foraging optimization algorithm-based novel feature selection approach for glaucoma classification from fundus images. Soft Computing. 28(3). 2431–2467. 45 indexed citations

Khanna, Munish, et al.. (2023). PlaNet: a robust deep convolutional neural network model for plant leaves disease recognition. Multimedia Tools and Applications. 83(2). 4465–4517. 48 indexed citations

Khanna, Munish, et al.. (2023). Deep learning based computer-aided automatic prediction and grading system for diabetic retinopathy. Multimedia Tools and Applications. 82(25). 39255–39302. 38 indexed citations

Singh, Law Kumar, Munish Khanna, Shankar Thawkar, & Rekha Singh. (2023). Nature-inspired computing and machine learning based classification approach for glaucoma in retinal fundus images. Multimedia Tools and Applications. 82(27). 42851–42899. 29 indexed citations

Thawkar, Shankar, et al.. (2023). Breast cancer: A hybrid method for feature selection and classification in digital mammography. International Journal of Imaging Systems and Technology. 33(5). 1696–1712. 15 indexed citations

10.

Singh, Law Kumar, Munish Khanna, & Rekha Singh. (2023). A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction. Measurement. 221. 113525–113525. 28 indexed citations

11.

Singh, Law Kumar, Pooja Sharma, Hitendra Garg, & Munish Khanna. (2022). Performance evaluation of various deep learning based models for effective glaucoma evaluation using optical coherence tomography images. Multimedia Tools and Applications. 81(19). 27737–27781. 26 indexed citations

12.

Singh, Law Kumar, Munish Khanna, & Shankar Thawkar. (2022). A novel hybrid robust architecture for automatic screening of glaucoma using fundus photos, built on feature selection and machine learning‐nature driven computing. Expert Systems. 39(10). 32 indexed citations

13.

Thawkar, Shankar, Satish J. Sharma, Munish Khanna, & Law Kumar Singh. (2021). Breast cancer prediction using a hybrid method based on Butterfly Optimization Algorithm and Ant Lion Optimizer. Computers in Biology and Medicine. 139. 104968–104968. 89 indexed citations

14.

Singh, Law Kumar, Munish Khanna, & Pooja Sharma. (2021). A novel multimodality based dual fusion integrated approach for efficient and early prediction of glaucoma. Biomedical Signal Processing and Control. 73. 103468–103468. 31 indexed citations

15.

Khanna, Munish, Naresh Chauhan, Dilip Kumar Sharma, & Law Kumar Singh. (2021). A Multi-Objective Approach for Test Suite Reduction During Testing of Web Applications. International Journal of Applied Metaheuristic Computing. 12(3). 81–122. 2 indexed citations

16.

Singh, Law Kumar, Pooja Sharma, Hitendra Garg, & Munish Khanna. (2021). An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images. International Journal of E-Health and Medical Communications. 12(4). 32–59. 13 indexed citations

17.

Khanna, Munish, et al.. (2021). Radiologist-Level Two Novel and Robust Automated Computer-Aided Prediction Models for Early Detection of COVID-19 Infection from Chest X-ray Images. Arabian Journal for Science and Engineering. 48(8). 11051–11083. 32 indexed citations

18.

Khanna, Munish, et al.. (2018). A Novel Approach for Regression Testing of Web Applications. International Journal of Intelligent Systems and Applications. 10(2). 55–71. 1 indexed citations

19.

Khanna, Munish. (2017). Application of Ant Colony Algorithm in Regression Testing of Web Applications –A Novel Approach. WSEAS Transactions on Computers archive. 16. 1 indexed citations

20.

Khanna, Munish, et al.. (2017). Test case prioritisation during web application testing. International Journal of Computer Applications in Technology. 56(3). 230–230. 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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