Ngoc-Vuong Ho
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Research Areas
Biography and Research Information
OverviewAI-generated summary
Ngoc-Vuong Ho researches advanced computational techniques for medical imaging and data analysis. His work includes the development of Point-Unet, a context-aware point-based neural network designed for volumetric segmentation, with publications appearing in 2021 and 2022. Ho has also contributed to the creation of the FG-CXR dataset, which aligns with radiologist gaze patterns to improve interpretability in chest X-ray report generation, with publications from 2024. Additionally, he has worked on RSSep, a sequence-to-sequence model for simultaneous referring remote sensing segmentation and detection, with a publication projected for 2025. Ho collaborates with several researchers at the University of Arkansas at Fayetteville, including Tran-Dac-Thinh Phan, Ngan Le, Trong Thang Pham, and Nhat-Tan Bui, with whom he has co-authored multiple publications. His h-index is 2, with a total of 5 publications and 30 citations.
Metrics
- h-index: 2
- Publications: 5
- Citations: 31
Selected Publications
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RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection (2025)
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FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation (2024)
Collaboration Network
Top Collaborators
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection
- RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection
- RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection
- RSSep: Sequence-to-Sequence Model for Simultaneous Referring Remote Sensing Segmentation and Detection
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