Beyond Damage Assessment: Recyclable Material Detection in Aerial Disaster Imagery Using a Lightweight Patch-Based Framework
This work addresses the niche problem of detecting recyclable materials in disaster zones for ecological purposes, but the results are preliminary and lack concrete performance numbers.
The paper presents a lightweight patch-based framework for detecting recyclable materials in aerial disaster imagery, providing a new publicly available dataset. Experimental results demonstrate the potential of the approach for localizing recyclable materials.
Nowadays, more and more disasters of different natures are appearing. Several disaster assessment approaches have been developed in order to identify damaged areas from aerial images. These damaged areas contain rich material that could be recycled towards several ecological purposes. In this paper, we present a lightweight approach that permits the efficient detection of recyclable material. Experimental results show the potential of the proposed approach towards localizing recyclable materials. Accordingly, we provide a rare dataset of material images that we labeled towards supporting the development of recyclable material detectors. The dataset of labeled material images is publicly available at: anonymous.