Rewa Sharma

448 citations
13 papers · 243 · 1 hit paper · h-index 3

Impact in

Papers in

Rewa Sharma

8 papers receiving 228 citations

Rewa Sharma's Hit Papers

A Systematic Review on Data Scarcity Problem in Deep Learning: Solution and Applications 2022 · 146 citations
1460+1+2Years since publication4080120

Peers

Rewa Sharma
Comparison fields: 5 of 87
  • Health Informatics 7
  • Information Systems 80
  • Computer Networks and Communications 58
  • Artificial Intelligence 77
  • Computer Vision and Pattern Recognition 36
Replace Srinath Doss with:
Srinath Doss Botswana
Stephen Jeswinde Nuagah Ghana
Nagat Drawel Canada
Sumit Srivastava India
Khaled Alhazmi Saudi Arabia
Fang Zhou China
Ankush Ghosh India
M. Vinoth Kumar India
Y. C. A. Padmanabha Reddy India
Amanpreet Singh India
Rewa Sharma relative to Srinath Doss Botswana Srinath Doss's profile →
Citations per field
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Srinath Doss · 1×
Citations per year

Countries citing papers authored by Rewa Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Rewa Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 5 scholars most cited alongside Rewa Sharma, 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 Rewa Sharma Line = papers co-authored together Rewa Sharma links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
A Systematic Review on Data Scarcity Problem in Deep Learning: Solution and Applications
Hit paper breakdown →
2022146
2 202184
3 20143
4 20242
5 20252
6 20142
7 20232
8 20231
9 20131
10 20240
11 20250
12 20220
13 20140

About Rewa Sharma

Rewa Sharma is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence, having authored 13 papers that have together received 243 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (5 papers), IoT and Edge/Fog Computing (4 papers), IoT-based Smart Home Systems (2 papers), Robotics and Sensor-Based Localization (2 papers), Imbalanced Data Classification Techniques (2 papers), Cloud Data Security Solutions (2 papers), Robotic Path Planning Algorithms (2 papers) and Smart Systems and Machine Learning (1 paper). The work is most often cited by research in Health Informatics (7 citations), Information Systems (80 citations), Computer Networks and Communications (58 citations), Artificial Intelligence (77 citations) and Computer Vision and Pattern Recognition (36 citations). Rewa Sharma has collaborated with scholars based in India. Frequent co-authors include Mamta Kathuria, Rajesh Kumar, Rajesh Kumar, Swati Jha and C. K. Jha. Their work appears in journals such as Journal of King Saud University - Computer and Information Sciences, ACM Computing Surveys, Environmental Modeling & Assessment and Computers & Electrical 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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