Continuous Learning Platform (CLP)

Continuous Learning Platform (CLP) 是一个由米兰比可卡大学信息、系统和通信系创建的数据集平台，旨在整合多个异构的人类活动识别数据集，以提供高质量、大规模的同质信号数据。该平台包含8个已整合的数据集，涵盖了多种活动类型和不同的数据来源。创建过程中，平台采用了信号和标签的同质化处理，确保数据的一致性和可用性。CLP的应用领域主要集中在人类活动识别，特别是通过深度学习技术提高活动分类的准确性和鲁棒性。

Continuous Learning Platform (CLP) is a dataset platform developed by the Department of Informatics, Systems and Communication of the University of Milano-Bicocca, aiming to integrate multiple heterogeneous human activity recognition datasets to provide high-quality, large-scale homogeneous signal data. The platform includes 8 integrated datasets, covering a diverse range of activity types and various data sources. During its development, the platform applies homogenization processing to signals and labels to ensure data consistency and availability. The primary application domains of CLP focus on human activity recognition, particularly improving the accuracy and robustness of activity classification through deep learning technologies.