M. Brown

1.0k citations
36 papers · 742 · h-index 14

Impact in

Papers in

M. Brown

33 papers receiving 659 citations

Peers

M. Brown
Comparison fields: 5 of 102
  • Human-Computer Interaction 84
  • Computer Vision and Pattern Recognition 269
  • Artificial Intelligence 303
  • Signal Processing 84
  • Information Systems 132
Replace Naveed Riaz with:
Naveed Riaz Pakistan
Mohamed Jamal Zemerly United Arab Emirates
Yuan Cheng China
Derek Hao Hu Hong Kong
Piotr Porwik Poland
Abdulaziz S. Almazyad Saudi Arabia
Yi-Leh Wu Taiwan
Martin R. Stytz United States
Nir Levine United States
Jeffrey S. Norris United States
M. Brown relative to Naveed Riaz Pakistan Naveed Riaz's profile →
Citations per field
00.5×2.5×
Naveed Riaz · 1×
Citations per year

Countries citing papers authored by M. Brown

Since Specialization
Citations

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

Fields of papers citing papers by M. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996209
2 2001138
3 198587
4 198353
5 201629
6 198228
7 199123
8 199219
9 198519
10 198217
11 199115
12 197714
13 199113
14 198613
15 20178
16 19967
17 20026
18 20025
19 20055
20 19875

About M. Brown

M. Brown is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Signal Processing and Aerospace Engineering, having authored 36 papers that have together received 742 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Speech Recognition and Synthesis (6 papers), Speech and dialogue systems (5 papers), Robotics and Sensor-Based Localization (4 papers), Handwritten Text Recognition Techniques (4 papers), Neural Networks and Applications (4 papers), Robot Manipulation and Learning (4 papers) and Time Series Analysis and Forecasting (4 papers). The work is most often cited by research in Human-Computer Interaction (84 citations), Computer Vision and Pattern Recognition (269 citations), Artificial Intelligence (303 citations), Signal Processing (84 citations) and Information Systems (132 citations). M. Brown has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Jianying Hu, William Turin, Sriram Ganapathy, L. R. Rabiner, Borys Omelayenko, Ying Ding, Ellen Schulten, Dieter Fensel, J. G. Wilpon and Sàdaf Noor. Their work appears in journals such as IEEE Transactions on Signal Processing, Operations Research, IEEE Intelligent Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence and Science & Justice.

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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