Hitendra Garg

6.6k citations
95 papers · 2.1k · h-index 23

Impact in

  • Hepatology top 1%
    • Liver Disease and Transplantation
    • Liver Disease Diagnosis and Treatment
    • Hepatitis B Virus Studies

Papers in

Hitendra Garg

86 papers receiving 2.0k citations

Peers

Hitendra Garg
Comparison fields: 5 of 119
  • Hepatology 645
  • Epidemiology 729
  • Pharmacology 162
  • Ophthalmology 134
  • Computer Vision and Pattern Recognition 284
Replace Binh P. Nguyen with:
Binh P. Nguyen New Zealand
Yadong Wang China
Ankush Mittal India
Ahmed Saeed United States
Wolfgang Ertel Germany
Yiming Wang China
Ruixuan Wang China
Venkatanareshbabu Kuppili India
Hitendra Garg relative to Binh P. Nguyen New Zealand Binh P. Nguyen's profile →
Citations per field
00.5×10×20×30×40×46.1×
Binh P. Nguyen · 1×
Citations per year

Countries citing papers authored by Hitendra Garg

Since Specialization
Citations

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

Fields of papers citing papers by Hitendra Garg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011271
2 2010189
3 2011143
4 202198
5 201595
6 202190
7 201390
8 202287
9 201283
10 201378
11 202256
12 201353
13 202149
14 202247
15 202345
16 201340
17 201134
18 202334
19 202231
20 202228

About Hitendra Garg

Hitendra Garg is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Information Systems, Ophthalmology and Signal Processing, having authored 95 papers that have together received 2.1k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (16 papers), Advanced Steganography and Watermarking Techniques (14 papers), Glaucoma and retinal disorders (14 papers), Chaos-based Image/Signal Encryption (10 papers), Liver Disease Diagnosis and Treatment (9 papers), Digital Imaging for Blood Diseases (9 papers), Liver Disease and Transplantation (6 papers) and Digital Media Forensic Detection (5 papers). The work is most often cited by research in Hepatology (645 citations), Epidemiology (729 citations), Pharmacology (162 citations), Ophthalmology (134 citations) and Computer Vision and Pattern Recognition (284 citations). Hitendra Garg has collaborated with scholars based in India, Taiwan and Bangladesh. Frequent co-authors include Shiv Kumar Sarin, Barjesh Chander Sharma, Vishal Garg, Ashish Kumar, Law Kumar Singh, Bhisham Sharma, Munish Khanna, Manoj Kumar, Nirupama Trehanpati and Archana Rastogi. Their work appears in journals such as Multimedia Tools and Applications, Journal of Gastroenterology and Hepatology, Hepatology International, Gastroenterology and Computers, materials & continua/Computers, materials & continua (Print).

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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