多光谱和智能感知
This book provides a concise overview of intelligent technologies for vision and sensing, with a particular focus on their applications in various multispectral configurations, including safety monitoring in rural areas. Within the realm of intelligent perception and contemporary healthcare, the book emphasizes the real-time monitoring, analysis, and prediction of vital signals using biomedical optical sensors. This approach aims to offer more adaptable and personalized services within the medical health management domain. Furthermore, the book delves into the comprehensive comprehension of physiological signals and additional data sources, such as environmental and motion data. The goal is to enhance the breadth and depth of data analysis, providing more integrated support for the life and health sector. Additionally, the book explores the implementation of edge intelligence algorithms at the sensor level to enable real-time analysis, enhancing the efficiency of sensor data processing and utilization. Detailed explanations of the configuration and deployment of an active vision camera system featuring an integrated edge algorithm are provided to elucidate the coordination and communication mechanisms of edge intelligence technology across multiple edge devices. A specific application case is then presented—the universal camera jamming system—which underscores the benefits of intelligent sensing fusion for tasks such as attitude and position recognition, as well as self-feedback excitation jamming.
这本书提供了一个智能技术对于视觉和传感领域的简洁概述,特别关注这些技术在各种多光谱配置中的应用,包括农村地区的安全监控。在智能感知领域及当代医疗保健中,本书强调利用生物医学光学传感器进行实时监测、分析和预测生命信号。这一方法旨在为医疗服务管理领域提供更加灵活且个性化的服务。此外,这本书深入探讨了生理信号及其他数据源的全面理解,例如环境和运动数据。目标是增强数据分析的广度和深度,从而为生活与健康领域提供更多集成支持。同时,本书探索在传感器层面实施边缘智能算法的方法来实现实时分析,以提升传感器数据处理和利用的效率。详细介绍了集成边缘算法的主动视觉摄像头系统配置和部署情况,以解释边缘智能技术在多种边缘设备之间协调和通信机制。然后呈现一个具体的应用案例——通用摄像干扰系统,强调了智能传感融合对于姿态和位置识别以及自我反馈干扰等任务的好处。
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