北科大電子所碩士生，共同指導老師 林信標 教授
黃耘宣目前就讀於國立台北科技大學電子工程系碩士班，專注於影像人工智慧技術的研究。大學期間，他以 C 語言進行影像處理相關開發，打下了扎實的基礎。
在碩士階段的研究中，他於林信標老師與裴重恩（Bui Trong An）教授的指導下，參與一項影像超解析度（Super-Resolution, SR）計畫，該計畫結合無人機（UAV/Drone）影像與衛星影像，以提升空間解析度。透過 Python 與深度學習框架，他訓練並評估模型，將無人機影像中的高頻細節與衛星影像的廣域資訊進行融合。
黃耘宣對高效且穩健的 AI 模型架構設計抱有濃厚興趣，特別關注輕量化網路、細節還原能力，以及模型在實際應用中之適應性。他也希望能將所開發的模型實現於 FPGA 平台上，進一步達成適用於邊緣裝置的高效能、低功耗硬體加速。
Yun-Hsuan Huang is currently a* master’s student in the Department of Electronic Engineering at National Taipei University of Technology*, focusing on research in image-based artificial intelligence technologies. During his undergraduate studies, he developed a strong foundation in image processing using the C programming language.
In his graduate research, he is working under the guidance of Professor Hsin-Piao Lin and Professor Bui Trong An on an image super-resolution (SR) project that combines UAV/Drone imagery with satellite images to enhance spatial resolution. By leveraging Python and deep learning frameworks, he trains and evaluates models that fuse high-frequency details from drone images with the broader contextual information of satellite data.
Yun-Hsuan is particularly interested in the design of efficient and robust AI model architectures, with a focus on lightweight networks, fine detail restoration, and ensuring adaptability in real-world deployment. He also aims to implement his models on FPGA platforms to achieve efficient, low-power hardware acceleration for edge applications.
Search for 黃耘宣 Yun-Hsuan Huang's papers on the Research page