Vidula Meshram

630 citations
17 papers · 356 · 1 hit paper · h-index 6

Impact in

Papers in

Vidula Meshram

15 papers receiving 339 citations

Vidula Meshram's Hit Papers

Machine learning in agriculture domain: A state-of-art survey 2021 · 213 citations
2130+1+3Years since publication50100150200

Peers

Vidula Meshram
Comparison fields: 5 of 83
  • Human-Computer Interaction 35
  • Analytical Chemistry 49
  • Plant Science 156
  • Cognitive Neuroscience 70
  • Computer Vision and Pattern Recognition 61
Replace Vishal Meshram with:
Vishal Meshram India
Analyn N. Yumang Philippines
Sabbir Ahmed Bangladesh
Fabrizio Balducci Italy
Dionis A. Padilla Philippines
Saumya Yadav India
Farruk Ahmed Bangladesh
Ahmed Abdelmoamen Ahmed United States
Jessie R. Balbin Philippines
Vidula Meshram relative to Vishal Meshram India Vishal Meshram's profile →
Citations per field
00.5×1.5×
Vishal Meshram · 1×
Citations per year

Countries citing papers authored by Vidula Meshram

Since Specialization
Citations

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

Fields of papers citing papers by Vidula Meshram

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Vidula Meshram, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vidula Meshram Line = papers co-authored together Vidula Meshram links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Machine learning in agriculture domain: A state-of-art survey
Hit paper breakdown →
2021213
2 201976
3 202214
4 202311
5 201610
6 20236
7 20235
8 20225
9 20234
10 20244
11 20233
12 20222
13 20241
14 20231
15 20211
16 20250
17 20240

About Vidula Meshram

Vidula Meshram is a scholar working on Computer Vision and Pattern Recognition, Plant Science, Cognitive Neuroscience, Computer Networks and Communications and Human-Computer Interaction, having authored 17 papers that have together received 356 indexed citations. Recurring topics across this work include Currency Recognition and Detection (8 papers), Smart Agriculture and AI (3 papers), Autism Spectrum Disorder Research (2 papers), Infection Control and Ventilation (1 paper), Green IT and Sustainability (1 paper), Hand Gesture Recognition Systems (1 paper), IoT and Edge/Fog Computing (1 paper) and Plant Physiology and Cultivation Studies (1 paper). The work is most often cited by research in Human-Computer Interaction (35 citations), Analytical Chemistry (49 citations), Plant Science (156 citations), Cognitive Neuroscience (70 citations) and Computer Vision and Pattern Recognition (61 citations). Vidula Meshram has collaborated with scholars based in India, Thailand and United States. Frequent co-authors include Kailas Patil, Vishal Meshram, Dinesh Bhagwan Hanchate, Prawit Chumchu, Amol Dhumane, Shripad Bhatlawande, Srinivas Ambala, Prashanth Vijayaraghavan, Ritesh Kumar and Sudeep D. Thepade. Their work appears in journals such as Data in Brief, IEEE Transactions on Human-Machine Systems, Revue d intelligence artificielle, Ingénierie des systèmes d information and Software Impacts.

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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