Duckweed Detection Dataset

Deficient domestic wastewater management, industrial waste, and floating debris are some leading factors that contribute to inland water pollution. The surplus of minerals and nutrients in overly contaminated zones can lead to the invasion of different invasive weeds. Lemnaceae, commonly known as duckweed, is a family of floating plants that has no leaves or stems and forms dense colonies with a fast growth rate. If not controlled, duckweed establishes a green layer on the surface and depletes fish and other organisms of oxygen and sunlight. In the last decades, duckweed blooms have become an expensive plague to remove in Lake Titicaca, causing significant biodiversity and economic losses. To address this issue, we propose the development of an unmanned surface vehicle (USV) to continuously monitor and collect duckweed. This device includes a steering angle estimation system (SAE) that combines a duckweed detector, a steering angle classifier, and a momentum-inspired module to determine continuously the orientation of the USV when it is inspecting a zone. We train and test our deep learning-based models with two novel datasets: first, a dataset for end-to-end steering angle classification collected synthetically using a bespoke simulator; and second, a dataset for duckweed detection. The latter is published in the present page for its reuse by the community. 

生活污水管理不善、工业废弃物与漂浮碎屑是造成内陆水污染的主要诱因之一。过度污染区域内矿物质与营养物质过剩，会催生多种外来入侵杂草。浮萍科（Lemnaceae）俗称浮萍，是一类无叶无茎的漂浮植物类群，生长速率快且能形成致密群落。若未加以管控，浮萍会在水面形成绿色覆盖层，耗尽鱼类与其他水生生物所需的氧气与阳光。近数十年来，的的喀喀湖（Lake Titicaca）的浮萍泛滥已成为治理成本高昂的难题，造成了严重的生物多样性与经济损失。为解决这一问题，我们提出开发一款无人水面艇（unmanned surface vehicle, USV），以实现对浮萍的持续监测与收集。该装置搭载转向角估计系统（steering angle estimation system, SAE），该系统结合了浮萍检测器、转向角分类器与动量启发模块，可在巡检作业区域时持续确定无人水面艇的航向。我们使用两个全新数据集对基于深度学习的模型开展训练与测试：其一为利用定制模拟器合成采集的端到端转向角分类数据集；其二为浮萍检测数据集。后者已发布于本页面，供社区重复使用。

搜集汇总

背景与挑战

背景概述

Duckweed Detection Dataset是一个用于计算机视觉中对象检测任务的数据集，专门针对浮萍（duckweed）的监测与识别。该数据集包含PNG格式的图像和TXT/XML格式的边界框标注，旨在支持无人水面艇（USV）在的的喀喀湖等水域进行浮萍检测和环境监控。数据集还提供了拍摄视角的CSV分类信息，适用于训练深度学习模型以解决浮萍泛滥导致的水污染问题。