Alam Noor
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
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- Advanced Neural Network Applications 4
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- IoT and Edge/Fog Computing 5
- Co-authors
- Anis Koubâa (5 shared papers)Yaqin Zhao (5 shared papers)Songhao Piao (2 shared papers)Rahim Khan (6 shared papers)Longwen Wu (4 shared papers)Ahmed Afifi (1 shared paper)Kai Li (5 shared papers)Wei Ni (3 shared papers)
- Journals
- Electronics (2 papers)Engineering Applications of Artificial Intelligence (1 paper)Wireless Communications and Mobile Computing (1 paper)Applied Sciences (1 paper)Multimedia Tools and Applications (1 paper)
- Partner nations
- ChinaPortugalSaudi Arabia
In The Last Decade
Alam Noor
25 papers receiving 552 citations
Peers
Comparison fields: 5 of 96
- Neurology 122
- Computer Vision and Pattern Recognition 180
- Health Information Management 23
- Small Animals 33
- Cognitive Neuroscience 81
Countries citing papers authored by Alam Noor
This map shows the geographic impact of Alam Noor'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 Alam Noor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alam Noor more than expected).
Fields of papers citing papers by Alam Noor
This network shows the impact of papers produced by Alam Noor. 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 Alam Noor. The network helps show where Alam Noor may publish in the future.
Co-authors
The 25 scholars most cited alongside Alam Noor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 104 | |
| 2 | 2020 | 71 | |
| 3 | 2020 | 56 | |
| 4 | 2022 | 51 | |
| 5 | 2021 | 44 | |
| 6 | 2021 | 38 | |
| 7 | 2019 | 30 | |
| 8 | 2020 | 27 | |
| 9 | 2020 | 26 | |
| 10 | 2021 | 20 | |
| 11 | 2020 | 19 | |
| 12 | 2024 | 13 | |
| 13 | 2020 | 12 | |
| 14 | 2022 | 8 | |
| 15 | 2014 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2021 | 5 | |
| 18 | 2023 | 5 | |
| 19 | 2021 | 4 | |
| 20 | 2023 | 4 |
About Alam Noor
Alam Noor is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Aerospace Engineering, Cognitive Neuroscience and Artificial Intelligence, having authored 27 papers that have together received 565 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (5 papers), Brain Tumor Detection and Classification (4 papers), UAV Applications and Optimization (4 papers), Advanced Neural Network Applications (4 papers), EEG and Brain-Computer Interfaces (4 papers), Animal Behavior and Welfare Studies (3 papers), Wireless Signal Modulation Classification (3 papers) and Advanced Image Fusion Techniques (3 papers). The work is most often cited by research in Neurology (122 citations), Computer Vision and Pattern Recognition (180 citations), Health Information Management (23 citations), Small Animals (33 citations) and Cognitive Neuroscience (81 citations). Alam Noor has collaborated with scholars based in China, Portugal and Saudi Arabia. Frequent co-authors include Anis Koubâa, Yaqin Zhao, Songhao Piao, Rahim Khan, Longwen Wu, Ahmed Afifi, Kai Li, Wei Ni, Xin Yuan and Bilel Benjdira. Their work appears in journals such as Electronics, Engineering Applications of Artificial Intelligence, Wireless Communications and Mobile Computing, Applied Sciences and Multimedia Tools and Applications.
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.