TGRSS ang DIOR remote sensing

DIOR is a large-scale benchmark dataset for optical remote sensing image target detection proposed by Han Jw's group at XIT. The dataset contains 23,463 images and 192,472 instances with an image size of 800×800 pixels and covers 20 object classes. Among them, the training set contains 5862 images, the validation set contains 5863 images, and the test set contains 11725 images. These 20 object classes are: Wind mill, Vehicle, Train station, Tennis court, Storage Tank, Ship, Harbor, Stadium, Ground Track Field, Golf course, Expressway toll station, Expressway service area, Dam, Chimney, Bridge, Overpass, Basketball Court, Baseball field, Airport, Airplane.DIOR是一款面向光学遥感图像目标检测的大规模基准数据集，由西安电子科技大学（XIT）韩Jw团队提出。该数据集共包含23463张图像与192472个目标标注实例，图像尺寸为800×800像素，涵盖20个目标类别。其中，训练集包含5862张图像，验证集包含5863张图像，测试集包含11725张图像。该数据集包含的20个目标类别分别为：风力发电机、车辆、火车站、网球场、储油罐、船舶、港口、体育场、田径场、高尔夫球场、高速公路收费站、高速公路服务区、大坝、烟囱、桥梁、立交桥、篮球场、棒球场、机场、飞机。

搜集汇总

背景与挑战

背景概述

DIOR是一个大规模光学遥感图像目标检测基准数据集，包含23,463张800×800像素的图像和192,472个实例，覆盖20个常见目标类别如风车、车辆和机场等。数据集分为训练集、验证集和测试集，适用于遥感领域的模型训练和评估。