WATT-EffNet: a lightweight and accurate model for classifying aerial disaster images

• Main Authors: Lee, Gao Yu, Dam, Tanmoy, Ferdaus, Md Meftahul, Poenar, Daniel Puiu, Duong, Vu N.
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Training; Computer Architecture
• Online Access: https://hdl.handle.net/10356/170684
• Institution: Nanyang Technological University

Incorporating deep learning (DL) classification models into unmanned aerial vehicles (UAVs) can significantly augment search-and-rescue operations and disaster management efforts. In such critical situations, the UAV's ability to promptly comprehend the crisis and optimally utilize its limit...