Ashim Saha

733 citations
32 papers · 379 indexed · h-index 9

Impact in

Papers in

Ashim Saha

30 papers receiving 350 citations

Peers

Ashim Saha
Comparison fields: 5 of 82
  • Computer Vision and Pattern Recognition 181
  • Experimental and Cognitive Psychology 54
  • Artificial Intelligence 110
  • Signal Processing 36
  • Health Informatics 4
Replace Wenju Zhou with:
Wenju Zhou China
Young-Tack Park South Korea
Ben Fielding United Kingdom
Minghao Wang China
J. Arturo Olvera-López Mexico
Chien‐Chang Hsu Taiwan
Mengmeng Ma China
Seong Tae Kim South Korea
Shikha Jain India
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Ashim Saha relative to Wenju Zhou China Wenju Zhou's profile →
Citations per field
00.5×2.6×
Wenju Zhou · 1×
Citations per year

Countries citing papers authored by Ashim Saha

Since Specialization
Citations

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

Fields of papers citing papers by Ashim Saha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Ashim Saha, 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 Ashim Saha Line = papers co-authored together Ashim Saha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 202417
4 20242
5 20245
6 20241
7 202322
8 20233
9 20231
10 202266
11 20224
12 202013
13 20187
14 20185
15 20165
16 201521
17 20148
18 201315
19 20127
20 2012101

About Ashim Saha

Ashim Saha is a scholar working on Computer Vision and Pattern Recognition, Health Informatics, Neurology, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 379 indexed citations. Recurring topics across this work include Face and Expression Recognition (8 papers), Context-Aware Activity Recognition Systems (4 papers), Human Pose and Action Recognition (4 papers), Face recognition and analysis (3 papers), Emotion and Mood Recognition (3 papers), Gait Recognition and Analysis (3 papers), Brain Tumor Detection and Classification (3 papers) and Chaos-based Image/Signal Encryption (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (181 citations), Experimental and Cognitive Psychology (54 citations), Artificial Intelligence (110 citations), Signal Processing (36 citations) and Health Informatics (4 citations). Ashim Saha has collaborated with scholars based in India, United States and Bangladesh. Frequent co-authors include Nirmalya Kar, Mrinal Kanti Debbarma, Apu Kumar Saha, Sanjoy Chakraborty, Sushmita Sharma, Sambhu Nath Pradhan, Praveen Kumar, Suman Deb, Ratul Chakraborty and Absalom E. Ezugwu. Their work appears in journals such as Multimedia Tools and Applications, Sadhana, Knowledge-Based Systems, Indian Journal of Science and Technology and Artificial Intelligence Review.

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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