Muhammad Amir As’ari

37 papers receiving 306 citations

Peers

Muhammad Amir As’ari
Comparison fields: 5 of 70
  • Computer Vision and Pattern Recognition 202
  • Artificial Intelligence 84
  • Biomedical Engineering 52
  • Radiology, Nuclear Medicine and Imaging 48
  • Orthopedics and Sports Medicine 32
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Tri Arief Sardjono Indonesia
Sreenivasan Ramasamy Ramamurthy United States
Adam Świtoński Poland
Wen-Jiin Tsai Taiwan
Antonio Hernández Zavala Mexico
Pierluigi Casale Netherlands
Michał Kępski Poland
Heba Shaban Egypt
Kalyani Bhole India
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Countries citing papers authored by Muhammad Amir As’ari

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Amir As’ari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Amir As’ari. 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 Muhammad Amir As’ari. The network helps show where Muhammad Amir As’ari may publish in the future.

Co-authorship network of co-authors of Muhammad Amir As’ari

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Amir As’ari. A scholar is included among the top collaborators of Muhammad Amir As’ari based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Muhammad Amir As’ari. Muhammad Amir As’ari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Esports Analytics on PlayerUnknown's Battlegrounds Player Placement Prediction using Machine Learning
3
13 1
14 23
15 6
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Wearable Device for Malaysian Ringgit Banknotes Recognition Based on Embedded Decision Tree Classifier
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Evaluation of Kinect Sensor in Mechanical Horse Simulator for Equine-Assisted Therapy
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Image Based Ringgit Banknote Recognition for Visually Impaired
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About Muhammad Amir As’ari

Muhammad Amir As’ari is a scholar working on Computer Vision and Pattern Recognition, Physical Therapy, Sports Therapy and Rehabilitation and Human-Computer Interaction, having authored 44 papers that have together received 324 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (12 papers), Anomaly Detection Techniques and Applications (9 papers) and Context-Aware Activity Recognition Systems (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (202 citations), Orthopedics and Sports Medicine (32 citations) and Human-Computer Interaction (20 citations). Muhammad Amir As’ari has collaborated with scholars based in Malaysia, Iraq and India. Frequent co-authors include Tan Tian Swee, Usman Ullah Sheikh, Wan Hazabbah Wan Hitam, Eko Supriyanto, B. Kermanshahi, Nasrul Humaimi Mahmood, Lokman Hakim Ismail, S. A. R. Abu–Bakar, R. Yokoyama and Yoshikatsu Akiyama. Their work appears in journals such as IEEE Access, Sensors and Image and Vision Computing.

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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