Lalit Mohan Goyal

1.9k total citations
41 papers, 1.2k citations indexed

About

Lalit Mohan Goyal is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lalit Mohan Goyal has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 11 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lalit Mohan Goyal's work include Data Mining Algorithms and Applications (6 papers), Imbalanced Data Classification Techniques (3 papers) and Rough Sets and Fuzzy Logic (3 papers). Lalit Mohan Goyal is often cited by papers focused on Data Mining Algorithms and Applications (6 papers), Imbalanced Data Classification Techniques (3 papers) and Rough Sets and Fuzzy Logic (3 papers). Lalit Mohan Goyal collaborates with scholars based in India, United States and Italy. Lalit Mohan Goyal's co-authors include Mamta Mittal, D. Jude Hemanth, Amit Verma, Iqbaldeep Kaur, Sudipta Roy, Muhammad Attique Khan, Jasleen Kaur Sethi, Bhavneet Kaur, Suresh Chandra Satapathy and Tai-hoon Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Lalit Mohan Goyal

39 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lalit Mohan Goyal India 19 346 320 149 140 134 41 1.2k
Gaurav Gupta India 19 252 0.7× 376 1.2× 139 0.9× 182 1.3× 224 1.7× 88 1.4k
Mohammed A. Al Ghamdi Saudi Arabia 22 355 1.0× 377 1.2× 287 1.9× 181 1.3× 173 1.3× 102 1.8k
Hanan Aljuaid Saudi Arabia 19 317 0.9× 544 1.7× 192 1.3× 72 0.5× 213 1.6× 71 1.3k
Ramesh Chandra Poonia India 22 255 0.7× 449 1.4× 166 1.1× 74 0.5× 216 1.6× 129 1.7k
Anupam Kumar Bairagi Bangladesh 25 240 0.7× 539 1.7× 235 1.6× 83 0.6× 427 3.2× 70 2.0k
Vijendra Singh India 19 427 1.2× 564 1.8× 167 1.1× 58 0.4× 180 1.3× 80 1.6k
M. M. Kamruzzaman Saudi Arabia 22 191 0.6× 276 0.9× 244 1.6× 48 0.3× 151 1.1× 87 1.6k
Madallah Alruwaili Saudi Arabia 19 179 0.5× 326 1.0× 105 0.7× 72 0.5× 204 1.5× 57 973
Alhadi Bustamam Indonesia 16 247 0.7× 432 1.4× 104 0.7× 104 0.7× 377 2.8× 142 1.2k
Saad Alanazi Saudi Arabia 20 145 0.4× 376 1.2× 132 0.9× 62 0.4× 165 1.2× 84 1.1k

Countries citing papers authored by Lalit Mohan Goyal

Since Specialization
Citations

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

Fields of papers citing papers by Lalit Mohan Goyal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lalit Mohan Goyal. 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 Lalit Mohan Goyal. The network helps show where Lalit Mohan Goyal may publish in the future.

Co-authorship network of co-authors of Lalit Mohan Goyal

This figure shows the co-authorship network connecting the top 25 collaborators of Lalit Mohan Goyal. A scholar is included among the top collaborators of Lalit Mohan Goyal 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 Lalit Mohan Goyal. Lalit Mohan Goyal 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.
Goyal, Lalit Mohan, et al.. (2023). How machine learning is used to study addiction in digital healthcare: A systematic review. International Journal of Information Management Data Insights. 3(2). 100175–100175. 18 indexed citations
2.
Mittal, Mamta, Gopi Battineni, Usharani Bhimavarapu, & Lalit Mohan Goyal. (2022). Text Analysis with Python: A Research Oriented Guide. BENTHAM SCIENCE PUBLISHERS eBooks. 2 indexed citations
3.
Goyal, Lalit Mohan, et al.. (2021). Real Time Fuzzy based Intelligent Parking Detection System Using Deep Learning Techniques. International Journal of Fuzzy Systems. 24(5). 2560–2568. 2 indexed citations
4.
Goyal, Lalit Mohan, et al.. (2021). Estimating the prevalence of stress among Indian students during the COVID-19 pandemic: A cross-sectional study from India. Journal of Taibah University Medical Sciences. 16(2). 260–267. 31 indexed citations
5.
Khosla, P.K., et al.. (2021). Predictive and Preventive Measures for Covid-19 Pandemic. Algorithms for intelligent systems. 12 indexed citations
6.
Goyal, Lalit Mohan, et al.. (2020). Factors affecting digital education during COVID-19: A statistical modeling approach. 22 indexed citations
7.
Mittal, Mamta, et al.. (2020). Corona Virus - SARS-CoV-2: An Insight to Another way of Natural Disaster. SHILAP Revista de lepidopterología. 6(22). e4–e4. 35 indexed citations
8.
Goyal, Lalit Mohan, et al.. (2020). Morphological classification of galaxies using Conv-nets. Earth Science Informatics. 13(4). 1427–1436. 5 indexed citations
9.
Mittal, Mamta, et al.. (2020). Cloud-based framework to mitigate the impact of COVID-19 on seafarers’ mental health. International Maritime Health. 71(3). 213–214. 20 indexed citations
10.
Agarwal, Aman, et al.. (2020). Fake News Detection Using a Blend of Neural Networks: An Application of Deep Learning. SN Computer Science. 1(3). 70 indexed citations
11.
Mittal, Mamta, Amit Verma, Iqbaldeep Kaur, et al.. (2020). Image Watermarking in Curvelet Domain Using Edge Surface Blocks. Symmetry. 12(5). 822–822. 13 indexed citations
12.
Khan, Muhammad Attique, Fawad Ahmed, Mamta Mittal, et al.. (2019). Gastrointestinal diseases segmentation and classification based on duo-deep architectures. Pattern Recognition Letters. 131. 193–204. 123 indexed citations
13.
Mittal, Mamta, Lalit Mohan Goyal, D. Jude Hemanth, & Jasleen Kaur Sethi. (2019). Clustering approaches for high‐dimensional databases: A review. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 9(3). 53 indexed citations
14.
Mittal, Mamta, et al.. (2019). Mixed Pixel Decomposition Based on Extended Fuzzy Clustering for Single Spectral Value Remote Sensing Images. Journal of the Indian Society of Remote Sensing. 47(3). 427–437. 30 indexed citations
15.
Mittal, Mamta, et al.. (2019). Deep learning based enhanced tumor segmentation approach for MR brain images. Applied Soft Computing. 78. 346–354. 179 indexed citations
16.
Kaur, Bhavneet, Meenakshi Sharma, Mamta Mittal, et al.. (2018). An improved salient object detection algorithm combining background and foreground connectivity for brain image analysis. Computers & Electrical Engineering. 71. 692–703. 30 indexed citations
17.
Mittal, Mamta, et al.. (2018). Opinion Mining for the Tweets in Healthcare Sector using Fuzzy Association Rule. EAI Endorsed Transactions on Pervasive Health and Technology. 4(16). e2–e2. 16 indexed citations
18.
Kumar, Raghvendra, Lê Hoàng Sơn, Sudan Jha, Mamta Mittal, & Lalit Mohan Goyal. (2018). Spatial data analysis using association rule mining in distributed environments: a privacy prospect. Spatial Information Research. 26(6). 629–638. 4 indexed citations
19.
Mittal, Mamta, et al.. (2017). A Comparative Study on Speech Output System “Emacspeak”. Global Journal of Enterprise Information System. 9(2). 54–54. 1 indexed citations
20.
Goyal, Lalit Mohan & M. M. Sufyan Beg. (2014). Improved filtration step for mining association rules. 1–4. 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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