Vimal K. Shrivastava

2.0k total citations
41 papers, 1.4k citations indexed

About

Vimal K. Shrivastava is a scholar working on Artificial Intelligence, Media Technology and Plant Science. According to data from OpenAlex, Vimal K. Shrivastava has authored 41 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 10 papers in Media Technology and 10 papers in Plant Science. Recurrent topics in Vimal K. Shrivastava's work include Psoriasis: Treatment and Pathogenesis (9 papers), Remote-Sensing Image Classification (8 papers) and Systemic Lupus Erythematosus Research (6 papers). Vimal K. Shrivastava is often cited by papers focused on Psoriasis: Treatment and Pathogenesis (9 papers), Remote-Sensing Image Classification (8 papers) and Systemic Lupus Erythematosus Research (6 papers). Vimal K. Shrivastava collaborates with scholars based in India, United States and Italy. Vimal K. Shrivastava's co-authors include Monoj K. Pradhan, Narendra D. Londhe, Jasjit S. Suri, Rajendra S. Sonawane, Sonajharia Minz, Mamta Thakur, M. K. Pradhan, K. Parvathi, Shoaib Shafique and Tadashi Araki and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Vimal K. Shrivastava

33 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vimal K. Shrivastava India 19 433 238 215 206 173 41 1.4k
Mona Soliman Egypt 17 159 0.4× 123 0.5× 129 0.6× 58 0.3× 41 0.2× 102 1.1k
Piotr M. Szczypiński Poland 16 269 0.6× 283 1.2× 1.4k 6.5× 268 1.3× 475 2.7× 37 2.5k
İlker Ali Özkan Türkiye 14 275 0.6× 215 0.9× 58 0.3× 226 1.1× 27 0.2× 41 951
Artur Klepaczko Poland 10 168 0.4× 116 0.5× 474 2.2× 138 0.7× 163 0.9× 31 1.1k
Rizwan Qureshi Pakistan 18 57 0.1× 165 0.7× 168 0.8× 34 0.2× 170 1.0× 90 1.4k
Adel Hafiane France 22 892 2.1× 240 1.0× 158 0.7× 232 1.1× 14 0.1× 70 1.9k
Ken Kobayashi Japan 21 335 0.8× 33 0.1× 105 0.5× 26 0.1× 149 0.9× 140 1.5k
Xiaoling Xia China 19 120 0.3× 170 0.7× 82 0.4× 17 0.1× 40 0.2× 84 1.2k
Mohammad Hesam Hesamian Australia 5 140 0.3× 378 1.6× 517 2.4× 51 0.2× 140 0.8× 11 1.3k
Wenle Wang China 21 174 0.4× 104 0.4× 384 1.8× 12 0.1× 828 4.8× 53 2.4k

Countries citing papers authored by Vimal K. Shrivastava

Since Specialization
Citations

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

Fields of papers citing papers by Vimal K. Shrivastava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vimal K. Shrivastava. 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 Vimal K. Shrivastava. The network helps show where Vimal K. Shrivastava may publish in the future.

Co-authorship network of co-authors of Vimal K. Shrivastava

This figure shows the co-authorship network connecting the top 25 collaborators of Vimal K. Shrivastava. A scholar is included among the top collaborators of Vimal K. Shrivastava 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 Vimal K. Shrivastava. Vimal K. Shrivastava 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.
2.
Shrivastava, Vimal K., et al.. (2023). A fine tuning approach using modified DenseNet model for skin cancer classification. International Journal of Medical Engineering and Informatics. 15(4). 323–335. 2 indexed citations
3.
Shrivastava, Vimal K., et al.. (2022). Management of the Brinjal Shoot and Fruit Borer Leucinodes orbonalis (Guen.) through Newer Insecticides in Brinjal. International Journal of Plant & Soil Science. 996–1004. 2 indexed citations
4.
Shrivastava, Vimal K., et al.. (2022). Diagnosis of COVID-19 using chest X-ray images based on modified DarkCovidNet model. Evolutionary Intelligence. 16(3). 729–738. 19 indexed citations
5.
Shrivastava, Vimal K., et al.. (2022). A novel Parametric Flatten-p Mish activation function based deep CNN model for brain tumor classification. Computers in Biology and Medicine. 150. 106183–106183. 41 indexed citations
6.
Pradhan, Monoj K., Sonajharia Minz, & Vimal K. Shrivastava. (2020). Entropy Query by Bagging-Based Active Learning Approach in the Extreme Learning Machine Framework for Hyperspectral Image Classification. Current Science. 119(6). 934–934. 3 indexed citations
7.
Pradhan, Monoj K., Sonajharia Minz, & Vimal K. Shrivastava. (2019). A Kernel-Based Extreme Learning Machine Framework for Classification of Hyperspectral Images Using Active Learning. Journal of the Indian Society of Remote Sensing. 47(10). 1693–1705. 7 indexed citations
8.
Shrivastava, Vimal K., M. K. Pradhan, Sonajharia Minz, & Mamta Thakur. (2019). RICE PLANT DISEASE CLASSIFICATION USING TRANSFER LEARNING OF DEEP CONVOLUTION NEURAL NETWORK. SHILAP Revista de lepidopterología. XLII-3/W6. 631–635. 158 indexed citations
9.
Pradhan, Monoj K., Sonajharia Minz, & Vimal K. Shrivastava. (2018). Fast active learning for hyperspectral image classification using extreme learning machine. IET Image Processing. 13(4). 549–555. 9 indexed citations
10.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2017). A novel and robust Bayesian approach for segmentation of psoriasis lesions and its risk stratification. Computer Methods and Programs in Biomedicine. 150. 9–22. 83 indexed citations
11.
Shrivastava, Vimal K., et al.. (2016). Factors affecting the accuracy of automatic signature verification. International Conference on Computing for Sustainable Global Development. 1805–1808. 2 indexed citations
12.
Araki, Tadashi, Nobutaka Ikeda, Pankaj K. Jain, et al.. (2016). PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology. Computer Methods and Programs in Biomedicine. 128. 137–158. 64 indexed citations
13.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2016). Reliability analysis of psoriasis decision support system in principal component analysis framework. Data & Knowledge Engineering. 106. 1–17. 10 indexed citations
14.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2016). Computer-aided diagnosis of psoriasis skin images with HOS, texture and color features: A first comparative study of its kind. Computer Methods and Programs in Biomedicine. 126. 98–109. 102 indexed citations
15.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2015). First review on psoriasis severity risk stratification: An engineering perspective. Computers in Biology and Medicine. 63. 52–63. 42 indexed citations
16.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2015). Reliable and accurate psoriasis disease classification in dermatology images using comprehensive feature space in machine learning paradigm. Expert Systems with Applications. 42(15-16). 6184–6195. 62 indexed citations
17.
Araki, Tadashi, Nobutaka Ikeda, Narendra D. Londhe, et al.. (2015). A new method for IVUS-based coronary artery disease risk stratification: A link between coronary & carotid ultrasound plaque burdens. Computer Methods and Programs in Biomedicine. 124. 161–179. 44 indexed citations
18.
Shrivastava, Vimal K., Narendra D. Londhe, Rajendra S. Sonawane, & Jasjit S. Suri. (2015). Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm. Computers in Biology and Medicine. 65. 54–68. 47 indexed citations
19.
Choudhary, Ritesh Kumar, et al.. (2005). Studies on field evaluation of imidacloprid (Confidor 17.8 SL) against sucking pests of cotton in rainfed condition.. Journal of Cotton Research and Development. 19(2). 241–243. 1 indexed citations
20.
Choudhary, Ritesh Kumar, et al.. (2005). Evaluation of bioefficacy of flubendiamide 20 WDG (Ril 038) against bollworms on cotton.. Journal of Cotton Research and Development. 19(2). 231–233.

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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