厦门市思明区近邻社区管理系统社区主体信息|社区管理数据集|居民信息数据集
收藏PASCAL VOC 2007
这个挑战的目标是从现实场景中的许多视觉对象类别中识别对象(即不是预先分割的对象)。它基本上是一个监督学习问题,因为它提供了一组标记图像的训练集。已选择的 20 个对象类别是: 人:人 动物:鸟、猫、牛、狗、马、羊 交通工具:飞机、自行车、船、公共汽车、汽车、摩托车、火车 室内:瓶子、椅子、餐桌、盆栽、沙发、电视/显示器 将有两个主要比赛和两个较小规模的“品酒师”比赛。内容:提供的训练数据由一组图像组成;每个图像都有一个注释文件,为图像中存在的 20 个类别之一中的每个对象提供一个边界框和对象类别标签。请注意,来自多个类的多个对象可能出现在同一图像中。
OpenDataLab 收录
MRMR
MRMR是一个专家级的多学科多模态检索基准,包含1502个经过人类专家仔细验证的查询,涵盖了23个领域。与之前的基准相比,MRMR在三个关键方面取得了进步:首先,它挑战了跨多个专业领域的检索系统,能够在不同领域之间进行细粒度的模型比较;其次,查询是推理密集型的,需要更深入地解释图像,例如诊断显微镜幻灯片;此外,还引入了矛盾检索这一新型任务,要求模型识别冲突的概念。与仅限于单个图像或单模态文档的早期基准不同,MRMR提供了一个具有多图像查询和混合模态语料库文档的现实场景。
arXiv 收录
MIMII数据集
MIMII数据集是由日立有限公司研究与开发集团创建的,专注于工业机器异常声音检测的数据集。该数据集包含26,092个正常操作条件下的声音文件,涵盖阀门、泵、风扇和滑轨四种机器类型。数据集的创建过程中,使用了TAMAGO-03麦克风阵列进行声音采集,并在多个真实工厂环境中混合背景噪声以模拟实际环境。MIMII数据集主要用于机器学习和信号处理社区开发自动化设施维护系统,特别是在无监督学习场景下检测机器异常声音。
arXiv 收录
Ninapro dataset 5 (double Myo armband)
The 5th Ninapro database includes 10 intact subjects recorded with two Thalmic Myo (https://www.myo.com/) armbands. The database can be used to test the Myo armbands separately as well. The database is thoroughly described in the paper: "Pizzolato et al., Comparison of Six Electromyography Acquisition Setups on Hand Movement Classification Tasks, Plos One 2017 (accepted).". Please, cite this paper for any work related to the 5th Ninapro database. The dataset is part of the Ninapro database (http://ninapro.hevs.ch/). Please, look at the database for more information. Acquisition Protocol The subjects have to repeat several movements represented by movies that are shown on the screen of a laptop. The experiment is divided in three exercises: 1. Basic movements of the fingers 2. Isometric, isotonic hand configurations and basic wrist movements 3. Grasping and functional movements During the acquisition, the subjects were asked to repeat the movements with the right hand. Each movement repetition lasted 5 seconds and was followed by 3 seconds of rest. The protocol includes 6 repetitions of 52 different movements (plus rest) performed by 10 intact subjects. The movements were selected from the hand taxonomy as well as from hand robotics literature. Acquisition Setup The muscular activity is gathered using 2 Thalmic Myo armbands. The database can be used to test the Myo armbands separately as well. The subjects in this database wore two Myo armbands one next to the other, including 16 active single–differential wireless electrodes. The top Myo armband is placed closed to the elbow with the first sensor placed on the radio humeral joint, as in the standard Ninapro configuration for the equally spaced electrodes; the second Myo armband is placed just after the first, nearer to the hand, tilted of 22.5 degrees. This configuration provides an extended uniform muscle mapping at an extremely affordable cost. The Myo sensors do not require the arm to be shaved and after few minutes the armband tighten very firmly to the arm of the subject. The sEMG signals are sampled at a rate of 200 Hz. The kinematic information is recorded with a dataglove (22 sensors Cyberglove 2). The cyberglove signal corresponds to raw data from the cyberglove sensors located as shown in the following pictures. The raw data are declared to be proportional to the angles at the joints in the CyberGlove manual. Data Sets For each exercise, for each subject, the database contains one matlab file with synchronized variables. The variables included in the matlab files are: • subject: the subject number; • sensor: the name of the sEMG sensor; • frequency: the frequency in Hertz of the recorded data • exercise: exercise number; • emg: sEMG signal. Columns 1-8 are the electrodes equally spaced around the forearm at the height of the radio humeral joint. Columns 9-16 represent the second Myo, tilted by 22.5 degrees clockwise. • acc (3 columns): raw signals from the three axis accelerometer of the first Myo, found in the Myo DB • glove (22 columns): uncalibrated signal from the 22 sensors of the CyberGlove. The raw data are declared to be proportional to the angles of the joints in the CyberGlove manual. • stimulus: the original label of the movement repeated by the subject; • restimulus: the corrected stimulus, processed with movement detection algorithms; • repetition: stimulus repetition index; • rerepetition: restimulus repetition index; • age: subject’s age; • gender: subject’s gender, ”m” for male ”f” for female; • weight: subject’s weight in kilograms; • height: subject’s height in centimeters; • laterality: subject’s laterality, ”r” for right-handed, ”l” for left-handed; • circumference: circumference of the subject’s forearm at the radio-humeral joint height, measured in centimeters;
Mendeley Data 收录
Yahoo Finance
Dataset About finance related to stock market
kaggle 收录
