Yonggang Wen
Biographic Data
| ID | 10137348 |
|---|---|
| NAME | Yonggang Wen |
| GIVEN NAMES | Yonggang |
| FAMILY NAME | Wen |
| SIGNATURE | WEN Y |
| AFFILIATIONS | Nanyang Technological University |
| ORCID | 0000-0002-2751-5114 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Multi-view dynastic classification and visual interpretation of blue-and-white porcelain
This study applies deep learning to classify—and interpret—blue-and-white porcelain images by dynastic period and studies the role of multiple object views. A multi-view dataset of Ming and Qing porcelain captured from different angles was curated, resulting in 284 objects and 963 images. Among the evaluated models, a pretrained and fine-tuned ResNet-50 (ImageNet1K-V2) achieved the best performance. Incorporating multiple views of the same object…
Key drivers and predictability of the unprecedented 2024 United Arab Emirates flood
In mid-April 2024, the Arabian Peninsula was struck by an extreme rainfall event, during which some areas received an entire year’s worth of precipitation within just 24 h. The United Arab Emirates was the hardest hit, experiencing widespread flooding, four fatalities, and economic damages exceeding USD 544 million. Analysis of multiple precipitation datasets confirmed that this was the most intense daily rainfall event ever recorded in the regio…
No prominent works on this page.
Key drivers and predictability of the unprecedented 2024 United Arab Emirates flood
In mid-April 2024, the Arabian Peninsula was struck by an extreme rainfall event, during which some areas received an entire year’s worth of precipitation within just 24 h. The United Arab Emirates was the hardest hit, experiencing widespread flooding, four fatalities, and economic damages exceeding USD 544 million. Analysis of multiple precipitation datasets confirmed that this was the most intense daily rainfall event ever recorded in the regio…
Multi-view dynastic classification and visual interpretation of blue-and-white porcelain
This study applies deep learning to classify—and interpret—blue-and-white porcelain images by dynastic period and studies the role of multiple object views. A multi-view dataset of Ming and Qing porcelain captured from different angles was curated, resulting in 284 objects and 963 images. Among the evaluated models, a pretrained and fine-tuned ResNet-50 (ImageNet1K-V2) achieved the best performance. Incorporating multiple views of the same object…
Building materials and conservation (1 works) · Climate variability and models (1 works) · Cultural Heritage Materials Analysis (1 works) · Flash flood (1 works) · Flood myth (1 works) · Geopotential (1 works) · Geopotential height (1 works) · Meteorological Phenomena and Simulations (1 works) · Orography (1 works) · Peninsula (1 works)