Md Abdul Masud

476 citations
33 papers · 311 · h-index 9

Impact in

Papers in

Md Abdul Masud

25 papers receiving 304 citations

Peers

Md Abdul Masud
Comparison fields: 5 of 72
  • Signal Processing 67
  • Artificial Intelligence 142
  • Information Systems 49
  • Computer Networks and Communications 48
  • Computer Vision and Pattern Recognition 41
Replace Mariacristina Gallo with:
Mariacristina Gallo Italy
Georg Krempl Germany
Evgenia Novikova Russia
Weiqi Zhang China
Mudassir Khan Saudi Arabia
Guozi Sun China
Negin Daneshpour Iran
Adán José-García France
Mohammad Ghasemzadeh Iran
Mieczysław A. Kłopotek Poland
Md Abdul Masud relative to Mariacristina Gallo Italy Mariacristina Gallo's profile →
Citations per field
00.5×1.5×2.1×
Mariacristina Gallo · 1×
Citations per year

Countries citing papers authored by Md Abdul Masud

Since Specialization
Citations

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

Fields of papers citing papers by Md Abdul Masud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Md Abdul Masud. 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 Md Abdul Masud. The network helps show where Md Abdul Masud may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201872
2 201942
3 201642
4 202341
5 201624
6 201914
7 201910
8 20188
9 20178
10 20207
11 20215
12 20195
13 20214
14 20224
15 20214
16 20213
17 20203
18 20193
19 20213
20 20202

About Md Abdul Masud

Md Abdul Masud is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Signal Processing, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 33 papers that have together received 311 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (6 papers), Anomaly Detection Techniques and Applications (5 papers), Antenna Design and Analysis (4 papers), Brain Tumor Detection and Classification (3 papers), Microwave Imaging and Scattering Analysis (3 papers), Energy Load and Power Forecasting (3 papers), COVID-19 diagnosis using AI (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Signal Processing (67 citations), Artificial Intelligence (142 citations), Information Systems (49 citations), Computer Networks and Communications (48 citations) and Computer Vision and Pattern Recognition (41 citations). Md Abdul Masud has collaborated with scholars based in Bangladesh, China and Malaysia. Frequent co-authors include Joshua Zhexue Huang, Zhong Ming, Xianghua Fu, Mohammad Sultan Mahmud, Jianqiang Li, Sajal Saha, Jing Li, Qingshan Jiang, Md Samsuzzaman and Rezaul Azim. Their work appears in journals such as IEEE Access, Information Sciences, Knowledge-Based Systems, Applied Soft Computing and Data & Knowledge 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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