Unlocking the capabilities of explainable few‑shot learning in remote sensing

• المؤلفون الرئيسيون: Lee, Gao Yu, Dam, Tanmoy, Md Meftahul Ferdaus, Poenar, Daniel Puiu, Duong, Vu N.
• مؤلفون آخرون: School of Mechanical and Aerospace Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Engineering; Deep learning; Explainable Artificial Intelligence (XAI); Few-shot learning; Remote sensing; Unmanned Aerial Vehicles (UAVs)
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/178366
• المؤسسة: Nanyang Technological University

Recent advancements have significantly improved the efficiency and effectiveness of deep learning methods for image-based remote sensing tasks. However, the requirement for large amounts of labeled data can limit the applicability of deep neural networks to existing remote sensing datasets. To ov...