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Ying-Chih Lai on Muck Rack

Ying-Chih Lai

As seen in: Wiley Online Library, MDPI, Chemistry World
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Articles

Vision‐Based Runway Detection and Localization for Aircraft Landing in Global Navigation Satellite System‐Denied Environments

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By Li-Wei Cheng, Ying-Chih Lai
| Wiley Online Library Verified
Data Availability Statement The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. References , , , , and . 2019. “ Runway Detection and Localization in Aerial Images Using Deep Learning.” In 2019 Digital Image Computing: Techniques and Applications (DICTA, 1–8. IEEE. , and . 2023.
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Deep Learning-Based Navigation System for Automatic Landing Approach of Fixed-Wing UAVs in GNSS-Denied Environments

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By Ying-Chih Lai, Ying-Xi Lin
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles s with Deep Learning and Risk Assessment

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By Ying-Chih Lai, Tzu-Yun Lin
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Ying-Chih Lai * and Tzu-Yun Lin Department of Aeronautics and Aeronautics, National Cheng Kung University, Tainan 701, Taiwan * Author to whom correspondence should be addressed. Remote Sens.
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