Chee‐Ming Ting

73 papers receiving 1.2k citations

Chee‐Ming Ting's Hit Papers

ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation 2024 · 290 citations
2900+1Years since publication50100150200250

Peers

Chee‐Ming Ting
Comparison fields: 5 of 75
  • Cognitive Neuroscience 465
  • Computer Vision and Pattern Recognition 274
  • Signal Processing 72
  • Computational Mathematics 4
  • Neurology 45
Replace Farhan Riaz with:
Farhan Riaz Pakistan
Ali Hassan Pakistan
Türker Tuncer Türkiye
Chikkannan Eswaran Malaysia
Fatma Lati̇foğlu Türkiye
Zümray Dokur Türkiye
Maheshkumar H. Kolekar India
Hossein Pourghassem Iran
Yaman Akbulut Türkiye
Rajeev Kr. Sharma United States
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Citations per field
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Farhan Riaz · 1×
Citations per year

Countries citing papers authored by Chee‐Ming Ting

Since Specialization
Citations

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

Fields of papers citing papers by Chee‐Ming Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee‐Ming Ting. 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 Chee‐Ming Ting. The network helps show where Chee‐Ming Ting may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation
Hit paper breakdown →
2024290
2 2019165
3 201977
4 202353
5 201645
6 202445
7 202443
8 201942
9 201739
10 200737
11 201036
12 201029
13 201628
14 201624
15 201724
16 201422
17 202416
18 201915
19 200714
20 201514

About Chee‐Ming Ting

Chee‐Ming Ting is a scholar working on Cognitive Neuroscience, Neurology, Artificial Intelligence, Computer Vision and Pattern Recognition and Sensory Systems, having authored 85 papers that have together received 1.3k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (26 papers), EEG and Brain-Computer Interfaces (16 papers), Speech Recognition and Synthesis (7 papers), Brain Tumor Detection and Classification (6 papers), Phonocardiography and Auscultation Techniques (4 papers), Biometric Identification and Security (4 papers), Control Systems and Identification (4 papers) and Target Tracking and Data Fusion in Sensor Networks (3 papers). The work is most often cited by research in Cognitive Neuroscience (465 citations), Computer Vision and Pattern Recognition (274 citations), Signal Processing (72 citations), Computational Mathematics (4 citations) and Neurology (45 citations). Chee‐Ming Ting has collaborated with scholars based in Malaysia, Saudi Arabia and Australia. Frequent co-authors include Hernando Ombao, Raphaël C.‐W. Phan, Fung Fung Ting, Sh‐Hussain Salleh, Fuad M. Noman, Chun‐Ren Phang, Alias Mohd Noor, Tan Tian Swee, Abd‐Krim Seghouane and Arifah Bahar. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, IEEE Journal of Biomedical and Health Informatics, IEEE Signal Processing Letters, Digital Signal Processing and IEEE Transactions on Medical Imaging.

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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