five

Human Activity Recognition

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arXiv2025-09-30 收录
下载链接:
https://github.com/srvcodes/continual-learning-benchmark/tree/master/datasets
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资源简介:
该数据集主要关注使用加速度计、陀螺仪和身体传感器读数进行人体活动识别的任务。在五个跨用户实验中,模型在一个用户的数据上进行训练,并在不同用户的数据上进行测试。每个样本包含9个通道和128个数据点,旨在完成人体活动识别的任务。

This dataset primarily focuses on the task of Human Activity Recognition (HAR) using readings from accelerometers, gyroscopes, and body-worn sensors. In five cross-user experiments, models are trained on data from one single user and tested on data from distinct users. Each sample comprises 9 channels and 128 data points, and is tailored for the human activity recognition task.
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