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Call for papers: Advanced bio-inspired deep learning algorithms for multi-modal perceptual big data analysis in car-driver assistance systems

Next generation cars collect a wide variety of data coming from different systems that need to be processed and merged in order to provide adequate car driving assistance. The thematic series will look at  approaches to car-driver assistance systems that make use of sophisticated bio-inspired algorithms and modern deep learning approaches.

Articles

  1. Authors: Chun-Wei Tsai, Chin-Feng Lai, Han-Chieh Chao and Athanasios V. Vasilakos

    Content type: Survey paper

Aims and scope

The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.

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