Cognitive diversity in perceptive informatics and affective computing

D. Hsu
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Abstract

The advent of sensor technologies and imaging modalities has greatly increased our ability to map the brain structure and understand its cognitive function. In order for the acquired Big Data (with large volume, wide variety, and high velocity) to be valuable, innovative data-centric algorithms and systems in machine learning, data mining and artificial intelligence have been developed, designed and implemented. Due to the complexity of the brain system and its cognitive processes, new data-driven paradigm is needed to recognize patterns in Big Data, to fuse information from different sources (systems and sensors), and to extract useful knowledge for actionable decisions.
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感知信息学和情感计算中的认知多样性
传感器技术和成像模式的出现大大提高了我们绘制大脑结构和理解其认知功能的能力。为了使获得的大数据(量大、种类多、速度快)有价值,机器学习、数据挖掘和人工智能领域的创新数据中心算法和系统已经被开发、设计和实施。由于大脑系统及其认知过程的复杂性,需要新的数据驱动范式来识别大数据中的模式,融合来自不同来源(系统和传感器)的信息,并为可操作的决策提取有用的知识。
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