Upal Mahbub

651 citations
32 papers · 306 indexed · h-index 11

Impact in

Papers in

Upal Mahbub

32 papers receiving 292 citations

Peers

Upal Mahbub
Comparison fields: 5 of 60
  • Human-Computer Interaction 51
  • Signal Processing 92
  • Computer Vision and Pattern Recognition 119
  • Computational Mechanics 45
  • Control and Systems Engineering 43
Replace Hafiz Imtiaz with:
Hafiz Imtiaz Bangladesh
Cristian Canton-­Ferrer Spain
T.S. Huang United States
Woosub Jung United States
Dohyung Kim South Korea
Zhimeng Zhang China
Hiroyasu Koshimizu Japan
Douglas Fidaleo United States
Yu Ling China
Yong-Ho Seo South Korea
Upal Mahbub relative to Hafiz Imtiaz Bangladesh Hafiz Imtiaz's profile →
Citations per field
00.5×4.1×
Hafiz Imtiaz · 1×
Citations per year

Countries citing papers authored by Upal Mahbub

Since Specialization
Citations

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

Fields of papers citing papers by Upal Mahbub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20241
3 20242
4 202312
5 202110
6 20208
7 201932
8 20132
9 201320
10 20134
11
Gesture recognition with depth images — A simple approach
20122
12 201213
13 20124
14 20124
15
Action recognition algorithm based on optical flow and RANSAC in frequency domain
201116
16 201137
17 201125
18 201016
19 20103
20 200911

About Upal Mahbub

Upal Mahbub is a scholar working on Human-Computer Interaction, Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 306 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (13 papers), Speech and Audio Processing (9 papers), Advanced Adaptive Filtering Techniques (8 papers), Gait Recognition and Analysis (7 papers), Hand Gesture Recognition Systems (7 papers), Video Surveillance and Tracking Methods (5 papers), Acoustic Wave Phenomena Research (4 papers) and Blind Source Separation Techniques (3 papers). The work is most often cited by research in Human-Computer Interaction (51 citations), Signal Processing (92 citations), Computer Vision and Pattern Recognition (119 citations), Computational Mechanics (45 citations) and Control and Systems Engineering (43 citations). Upal Mahbub has collaborated with scholars based in Bangladesh, United States and Japan. Frequent co-authors include Md Atiqur Rahman Ahad, Hafiz Imtiaz, Md. Ashfanoor Kabir, Shaikh Anowarul Fattah, Rama Chellappa, Jukka Komulainen, Md. Shafiur Rahman, Denzil Ferreira, Tauhidur Rahman and Celia Shahnaz. Their work appears in journals such as Pattern Recognition Letters, Computer Communications, IEEE Transactions on Biometrics Behavior and Identity Science, Neurocomputing and Circuits Systems and Signal Processing.

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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