Vikas Deep

674 citations
47 papers · 452 · h-index 11

Impact in

Papers in

Vikas Deep

43 papers receiving 419 citations

Peers

Vikas Deep
Comparison fields: 5 of 106
  • Health Information Management 60
  • Artificial Intelligence 127
  • Medical Laboratory Technology 5
  • Oncology 83
  • Computer Vision and Pattern Recognition 73
Replace Muhammad Sheraz Arshad Malik with:
Muhammad Sheraz Arshad Malik Pakistan
Mahamudul Hasan Bangladesh
Areej Alasiry Saudi Arabia
R. Suganya India
Muhammad Rukunuddin Ghalib India
Mina Younan Egypt
Fatma Helmy Ismail Egypt
Muhammad Golam Kibria Bangladesh
A. Harshavardhan India
Varun Malik India
Vikas Deep relative to Muhammad Sheraz Arshad Malik Pakistan Muhammad Sheraz Arshad Malik's profile →
Citations per field
00.5×12×
Muhammad Sheraz Arshad Malik · 1×
Citations per year

Countries citing papers authored by Vikas Deep

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Deep

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Vikas Deep, 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 Vikas Deep Line = papers co-authored together Vikas Deep links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020120
2 201651
3 201849
4 202030
5 202025
6 200322
7 201619
8 201814
9 201813
10 202111
11 201910
12 20167
13 20167
14
Expert system for the management of insect-pests in pulse crops
20156
15 20186
16 20166
17 20215
18
Expert Systems In Agriculture: An Overview
20145
19 20195
20 20184

About Vikas Deep

Vikas Deep is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 47 papers that have together received 452 indexed citations. Recurring topics across this work include IoT-based Smart Home Systems (4 papers), Network Security and Intrusion Detection (4 papers), Face and Expression Recognition (3 papers), Artificial Intelligence in Healthcare (3 papers), IoT and Edge/Fog Computing (3 papers), Cloud Computing and Resource Management (3 papers), IoT and GPS-based Vehicle Safety Systems (3 papers) and Software Engineering Research (3 papers). The work is most often cited by research in Health Information Management (60 citations), Artificial Intelligence (127 citations), Medical Laboratory Technology (5 citations), Oncology (83 citations) and Computer Vision and Pattern Recognition (73 citations). Vikas Deep has collaborated with scholars based in India, United Arab Emirates and Saudi Arabia. Frequent co-authors include Purushottam Sharma, Manoj Kumar, Mohammed Alshehri, Rayed AlGhamdi, Vinod Kumar Shukla, S. K. Gupta, Osama Alfarraj, Deepti Mehrotra, Naveen Garg and Renu Jain. Their work appears in journals such as Mobile Networks and Applications, Plant Foods for Human Nutrition, Concurrency and Computation Practice and Experience, Advances in intelligent systems and computing and Lecture notes in mechanical engineering.

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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