轻量级框架高效识别灾后航拍图像中的可回收材料
Beyond Damage Assessment: Recyclable Material Detection in Aerial Disaster Imagery Using a Lightweight Patch-Based Framework
- 基于局部图像块的轻量级检测方法，适合边缘设备部署
- 在自建数据集上实现高精度材料定位，支持灾后资源回收
- 公开了首个灾后可回收材料标注数据集，推动领域发展
近年来，各类灾害频发，已有多种方法用于从航拍图像中识别受损区域。这些受损区域含有大量可回收材料，可用于生态修复等目的。本文提出一种轻量级方法，高效检测灾后影像中的可回收材料。实验表明该方法能有效定位可回收物质。为此，我们构建并公开了一个全新的材料图像标注数据集，为可回收材料检测模型的研发提供支持。
原文摘要 · Abstract (English)
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.
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