Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Agricultural plant diseases identification: From traditional approach to deep learning
2023117 citationsJameer Kotwal, Ramgopal Kashyap et al.Materials Today Proceedingsprofile →
Artificial Driving based EfficientNet for Automatic Plant Leaf Disease Classification
202381 citationsJameer Kotwal, Ramgopal Kashyap et al.Multimedia Tools and Applicationsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of M. M. Pathan'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 M. M. Pathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. M. Pathan more than expected).
This network shows the impact of papers produced by M. M. Pathan. 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 M. M. Pathan. The network helps show where M. M. Pathan may publish in the future.
Co-authorship network of co-authors of M. M. Pathan
This figure shows the co-authorship network connecting the top 25 collaborators of M. M. Pathan.
A scholar is included among the top collaborators of M. M. Pathan 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 M. M. Pathan. M. M. Pathan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kotwal, Jameer, Ramgopal Kashyap, & M. M. Pathan. (2023). Agricultural plant diseases identification: From traditional approach to deep learning. Materials Today Proceedings. 80. 344–356.117 indexed citations breakdown →
Pathan, M. M., et al.. (2018). Assessment of hematological, biochemical and hormonal status of indigenous sheep during hot and cold dry season.. The Indian Veterinary Journal. 95(1). 46–48.
13.
Pathan, M. M., et al.. (2014). HEPATOPROTECTIVE ACTIVITY OF MAYTENUS EMARGINATA AGAINST PARACETAMOL INDUCED LIVER INJURY IN MALE WISTAR RATS. International Journal of Pharmacy and Pharmaceutical Sciences. 6(8). 320–323.3 indexed citations
14.
Pathan, M. M., et al.. (2013). Assessment of oxidative stress around parturition by determining antioxidant vitamins in Mehsana buffaloes. Indian Journal of Animal Research. 47(2). 156–159.1 indexed citations
15.
Pathan, M. M., et al.. (2011). COMPARATIVE STUDIES ON HAEMATO-BIOCHEMICAL PROFILE OF CYCLIC AND NON-CYCLIC HOLSTEIN-FRIESIAN CROSS-BRED COWS.5 indexed citations
16.
Chandra, Gulab, et al.. (2011). TANNINIFEROUS FEED RESOURCES IN DAIRY ANIMALS: A REVIEW. Agricultural Reviews. 32(4). 267–275.2 indexed citations
17.
Singh, Ashish Kumar, et al.. (2011). Bovine colostrum and neonate immunity - a review.. Agricultural Reviews. 32(2). 79–90.5 indexed citations
18.
Pathan, M. M., et al.. (2010). Plasma Trace Element Changes In Periparturient Mehsana Buffaloes. Indian Journal of Animal Nutrition. 27(2). 134–137.
19.
Pathan, M. M., et al.. (2010). ANTIOXIDANT STATUS IN PERIPARTURIENT MEHSANA BUFFALOES. 21(1). 748–751.5 indexed citations
20.
Pathan, M. M., et al.. (2010). Heat Shock Proteins and their clinical Implications. Veterinary World. 3(12). 558–560.6 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.