Van-Truong Pham

1.1k total citations
61 papers, 684 citations indexed

About

Van-Truong Pham is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Van-Truong Pham has authored 61 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Van-Truong Pham's work include Medical Image Segmentation Techniques (19 papers), AI in cancer detection (17 papers) and Advanced Neural Network Applications (13 papers). Van-Truong Pham is often cited by papers focused on Medical Image Segmentation Techniques (19 papers), AI in cancer detection (17 papers) and Advanced Neural Network Applications (13 papers). Van-Truong Pham collaborates with scholars based in Vietnam, Taiwan and United States. Van-Truong Pham's co-authors include Thi-Thao Tran, Kuo‐Kai Shyu, Ming-Ji Yang, Men‐Tzung Lo, Pa‐Chun Wang, Po‐Lei Lee, Chen Lin, Lian‐Yu Lin, Yung-Hung Wang and Wen‐Yih Isaac Tseng and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Industrial Electronics.

In The Last Decade

Van-Truong Pham

56 papers receiving 647 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Van-Truong Pham Vietnam 14 233 205 106 92 87 61 684
Hany S. Hussein Egypt 16 106 0.5× 283 1.4× 157 1.5× 49 0.5× 110 1.3× 70 683
Zhicheng Ma China 9 160 0.7× 146 0.7× 143 1.3× 83 0.9× 76 0.9× 69 514
Leandro A. Passos Brazil 15 229 1.0× 140 0.7× 211 2.0× 41 0.4× 142 1.6× 48 666
Necaattin Barışçı Türkiye 12 132 0.6× 120 0.6× 90 0.8× 100 1.1× 120 1.4× 57 525
Huijie Fan China 14 413 1.8× 39 0.2× 152 1.4× 22 0.2× 83 1.0× 53 818
Hiren Mewada Saudi Arabia 13 126 0.5× 209 1.0× 104 1.0× 28 0.3× 59 0.7× 105 630
M. Gorgoń Poland 15 338 1.5× 157 0.8× 132 1.2× 29 0.3× 39 0.4× 51 583
Xinyu Lin China 13 250 1.1× 36 0.2× 155 1.5× 27 0.3× 293 3.4× 58 773

Countries citing papers authored by Van-Truong Pham

Since Specialization
Citations

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

Fields of papers citing papers by Van-Truong Pham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Van-Truong Pham. 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 Van-Truong Pham. The network helps show where Van-Truong Pham may publish in the future.

Co-authorship network of co-authors of Van-Truong Pham

This figure shows the co-authorship network connecting the top 25 collaborators of Van-Truong Pham. A scholar is included among the top collaborators of Van-Truong Pham 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 Van-Truong Pham. Van-Truong Pham 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
1.
Tran, Thi-Thao, et al.. (2025). LiteNeXt: A novel lightweight ConvMixer-based model with Self-embedding Representation Parallel for medical image segmentation. Biomedical Signal Processing and Control. 107. 107773–107773. 3 indexed citations
2.
Nguyen, Van Quang, et al.. (2025). Mixmamba-fewshot: mamba and attention mixer-based method with few-shot learning for bearing fault diagnosis. Applied Intelligence. 55(7). 3 indexed citations
3.
Tran, Thi-Thao, et al.. (2025). GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation. Journal of Imaging Informatics in Medicine. 38(5). 3198–3220. 3 indexed citations
4.
5.
6.
Tran, Thi-Thao, et al.. (2025). DermoMamba: a cross-scale Mamba-based model with guide fusion loss for skin lesion segmentation in dermoscopy images. Pattern Analysis and Applications. 28(3). 1 indexed citations
7.
Pham, Van-Truong, et al.. (2024). CapNet: An Automatic Attention-Based with Mixer Model for Cardiovascular Magnetic Resonance Image Segmentation. Journal of Imaging Informatics in Medicine. 38(1). 94–123. 4 indexed citations
8.
Tran, Thi-Thao, et al.. (2024). Multilevel Few-Shot Model With Selective Aggregation Feature for Bearing Fault Diagnosis Under Limited Data Condition. IEEE Sensors Letters. 9(1). 1–4. 2 indexed citations
9.
Tran, Thi-Thao, et al.. (2024). SC-MambaFew: Few-shot learning based on Mamba and selective spatial-channel attention for bearing fault diagnosis. Computers & Electrical Engineering. 123. 110004–110004. 5 indexed citations
10.
Tran, Thi-Thao, et al.. (2023). Attention ConvMixer Model and Application for Fish Species Classification. SHILAP Revista de lepidopterología. 10(3). e2–e2. 10 indexed citations
11.
Pham, Van-Truong, et al.. (2023). A Fully Convolutional Network with Waterfall Atrous Spatial Pooling and Localized Active Contour Loss for Fish Segmentation. SHILAP Revista de lepidopterología. 10(1). e4–e4. 2 indexed citations
12.
Pham, Van-Truong, et al.. (2023). An EffcientNet-encoder U-Net Joint Residual Refinement Module with Tversky–Kahneman Baroni–Urbani–Buser loss for biomedical image Segmentation. Biomedical Signal Processing and Control. 83. 104631–104631. 18 indexed citations
13.
Lin, Chen, Thi-Thao Tran, Van-Truong Pham, et al.. (2020). Probing age-related changes in cardio-respiratory dynamics by multimodal coupling assessment. Chaos An Interdisciplinary Journal of Nonlinear Science. 30(3). 33118–33118. 7 indexed citations
14.
Pham, Van-Truong, Chen Lin, Thi-Thao Tran, et al.. (2020). Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging. Journal of Cardiology. 76(6). 601–609. 7 indexed citations
15.
Lin, Lian‐Yu, Mao‐Yuan Su, Van-Truong Pham, et al.. (2016). Endocardial Remodeling in Heart Failure Patients with Impaired and Preserved Left Ventricular Systolic Function-A Magnetic Resonance Image Study. Scientific Reports. 6(1). 20868–20868. 6 indexed citations
16.
Pham, Van-Truong, Thi-Thao Tran, Kuo‐Kai Shyu, et al.. (2016). Shape collaborative representation with fuzzy energy based active contour model. Engineering Applications of Artificial Intelligence. 56. 60–74. 5 indexed citations
17.
Chen, Yunn‐Jy, Tiffany Ting‐Fang Shih, Leh‐Kiong Huon, et al.. (2015). Acoustic-integrated dynamic MR imaging for a patient with obstructive sleep apnea. Magnetic Resonance Imaging. 33(10). 1350–1352. 4 indexed citations
18.
Huon, Leh‐Kiong, Van-Truong Pham, Yunn‐Jy Chen, et al.. (2014). Synchronized imaging and acoustic analysis of the upper airway in patients with sleep-disordered breathing. Physiological Measurement. 35(12). 2501–2512. 3 indexed citations
19.
Shyu, Kuo‐Kai, et al.. (2011). Fuzzy distribution fitting energy-based active contours for image segmentation. Nonlinear Dynamics. 69(1-2). 295–312. 5 indexed citations
20.
Pham, Van-Truong, et al.. (2010). Evaluation of active contour on medical inhomogeneous image segmentation. 17. 311–314. 4 indexed citations

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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