Deepika Ghai

904 citations
26 papers · 389 · h-index 9

Impact in

Papers in

Deepika Ghai

21 papers receiving 369 citations

Peers

Deepika Ghai
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 127
  • Neurology 34
  • Media Technology 35
  • Health Information Management 15
  • Artificial Intelligence 101
Replace Syam Machinathu Parambil Gangadharan with:
Syam Machinathu Parambil Gangadharan India
Radwa Marzouk Saudi Arabia
Chitapong Wechtaisong Thailand
G. Sajiv India
Kang Li China
Jeonghong Kim South Korea
Amin Alqudah Jordan
Nouf Abdullah Almujally Saudi Arabia
Vibhav Prakash Singh India
Kishor K. Bhoyar India
Deepika Ghai relative to Syam Machinathu Parambil Gangadharan India Syam Machinathu Parambil Gangadharan's profile →
Citations per field
00.5×4.3×
Syam Machinathu Parambil Gangadharan · 1×
Citations per year

Countries citing papers authored by Deepika Ghai

Since Specialization
Citations

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

Fields of papers citing papers by Deepika Ghai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021131
2 202260
3 202141
4 202239
5 202022
6 202218
7 202211
8 20219
9 20139
10 20228
11 20238
12 20198
13 20166
14
A REVIEW ON CLASSIFICATION OF LAND USE/LAND COVER CHANGE ASSESSMENT BASED ON NORMALIZED DIFFERENCE VEGETATION INDEX -
20206
15 20234
16 20173
17 20212
18
Comparative Analysis on Smart Helmet and Intelligent Biking System
20191
19 20241
20 20211

About Deepika Ghai

Deepika Ghai is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Ecology, Artificial Intelligence and Neurology, having authored 26 papers that have together received 389 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (5 papers), Image Retrieval and Classification Techniques (4 papers), Remote Sensing in Agriculture (4 papers), Image Processing and 3D Reconstruction (3 papers), Brain Tumor Detection and Classification (3 papers), Advanced Neural Network Applications (3 papers), Land Use and Ecosystem Services (3 papers) and Remote-Sensing Image Classification (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (127 citations), Neurology (34 citations), Media Technology (35 citations), Health Information Management (15 citations) and Artificial Intelligence (101 citations). Deepika Ghai has collaborated with scholars based in India, Saudi Arabia and Romania. Frequent co-authors include Sandeep Kumar, Shilpa Rani, Prashant Kumar Shukla, Priti Maheshwary, Jasminder Kaur Sandhu, Piyush Kumar Shukla, Arpit Jain, MVV Prasad Kantipudi, Amal H. Alharbi and Mohammad Aman Ullah. Their work appears in journals such as Multimedia Tools and Applications, International Journal of Computational Intelligence Systems, Computational Intelligence and Neuroscience, Journal of Information Security and Applications and Sustainability.

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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