V. Vaidehi

3.5k citations
227 papers · 2.3k · 1 hit paper · h-index 23

Impact in

Papers in

V. Vaidehi

212 papers receiving 2.1k citations

V. Vaidehi's Hit Papers

Diabetes Prediction using Machine Learning Algorithms 2019 · 274 citations
2740+2+4Years since publication50100150200250

Peers

V. Vaidehi
Comparison fields: 5 of 120
  • Health Information Management 267
  • Computer Networks and Communications 899
  • Signal Processing 387
  • Artificial Intelligence 778
  • Computer Vision and Pattern Recognition 474
Replace Yasha Wang with:
Yasha Wang China
Omar Cheikhrouhou Tunisia
Rizwan Patan India
Mian Ahmad Jan Pakistan
Shoab Ahmed Khan Pakistan
Muhammad Zakarya Pakistan
Mangal Sain South Korea
Hoon Jae Lee South Korea
Jiehan Zhou Finland
Kashif Nisar Malaysia
V. Vaidehi relative to Yasha Wang China Yasha Wang's profile →
Citations per field
00.5×9.3×
Yasha Wang · 1×
Citations per year

Countries citing papers authored by V. Vaidehi

Since Specialization
Citations

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

Fields of papers citing papers by V. Vaidehi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside V. Vaidehi, 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 V. Vaidehi Line = papers co-authored together V. Vaidehi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 227 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Diabetes Prediction using Machine Learning Algorithms
Hit paper breakdown →
2019274
2 2019140
3 201582
4 202048
5 201145
6 201443
7 202042
8 201241
9 200941
10 202437
11 202035
12 200135
13 202434
14 200631
15 201929
16 201328
17 201328
18 202025
19 201023
20 201323

About V. Vaidehi

V. Vaidehi is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Electrical and Electronic Engineering, having authored 227 papers that have together received 2.3k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (25 papers), Face and Expression Recognition (24 papers), Energy Efficient Wireless Sensor Networks (24 papers), Target Tracking and Data Fusion in Sensor Networks (23 papers), Anomaly Detection Techniques and Applications (23 papers), Video Surveillance and Tracking Methods (20 papers), Inertial Sensor and Navigation (19 papers) and Context-Aware Activity Recognition Systems (19 papers). The work is most often cited by research in Health Information Management (267 citations), Computer Networks and Communications (899 citations), Signal Processing (387 citations), Artificial Intelligence (778 citations) and Computer Vision and Pattern Recognition (474 citations). V. Vaidehi has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include D. Sangeetha, S. Sibi Chakkaravarthy, R. Bhargavi, P. T. V. Bhuvaneswari, P. Balamuralidhar, S. Srikanth, Ravi Ramesh Pathak, Balasubramanian Raman, R. Karthik and Suresh Chandra Satapathy. Their work appears in journals such as Wireless Personal Communications, Expert Systems with Applications, Sadhana, Journal of Intelligent & Fuzzy Systems and Multimedia Tools and Applications.

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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