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.
Classifying Crop Leaf Diseases using Different Deep Learning Models with Transfer Learning
2024809 citationsLakshin Pathak, Mili Virani et al.International Journal of Innovative Science and Research Technology (IJISRT)profile →
This map shows the geographic impact of Mili Virani'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 Mili Virani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mili Virani more than expected).
This network shows the impact of papers produced by Mili Virani. 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 Mili Virani. The network helps show where Mili Virani may publish in the future.
Co-authorship network of co-authors of Mili Virani
This figure shows the co-authorship network connecting the top 25 collaborators of Mili Virani.
A scholar is included among the top collaborators of Mili Virani 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 Mili Virani. Mili Virani is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Classifying Crop Leaf Diseases using Different Deep Learning Models with Transfer Learningbreakdown →
2024·International Journal of Innovative Science and Research Technology (IJISRT)·Lakshin Pathak,Mili Virani,(unknown)
809
About Mili Virani
Mili Virani is a scholar working on Signal Processing, Information Systems and Computer Networks and Communications, having authored 4 papers that have together received 811 indexed citations. Recurring topics across this work include Spam and Phishing Detection (1 paper), Smart Agriculture and AI (1 paper) and Artificial Intelligence in Law (1 paper). The work is most often cited by research in Health Informatics (10 citations), Safety Research (27 citations) and Complementary and Manual Therapy (7 citations). Mili Virani has collaborated with scholars based in India, Jordan and Iran. Frequent co-authors include Lakshin Pathak, Mohammad S. Obaidat, Nilesh Kumar Jadav, Sudeep Tanwar, Rajesh Gupta, Hossein Shahinzadeh and Jigna J. Hathaliya. Their work appears in journals such as International Journal of Innovative Science and Research Technology (IJISRT).
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.