Deep learning is a topic of broad interest, both to researchers who develop new deep architectures and learning algorithms, as well as to practitioners who apply deep learning models to a wide range of applications, from image classification to video tracking, etc. Brainlike computing combines computational techniques with cognitive ideas, principles and models inspired by the brain for building information systems used in humans’ common life. Pattern recognition is a conventional area of artificial intelligence, which focuses on the recognition of patterns and regularities in data. Recently, there has been very rapid and impressive progress in these three areas, in terms of both theories and applications, but many challenges remain. This special session aims at bringing together researchers in machine learning and related areas to discuss the utility of deep learning for brain-like computing and pattern recognition, the advances, the challenges we face, and to brainstorm about new solutions and directions.
Papers for this special session of IJCNN 2016 should be submitted electronically through the Congress website at www.wcci2016.org. Please submit your paper to the special session: Deep Learning for Brain-Like Computing and Pattern Recognition.
We can only accept PDF files. The maximum number of pages is eight (8) and maximum file size is 10MB. Up to two additional pages will be permitted for a charge of USD 100 per additional page payable at the registration time. Illustrations and references are included in the page count. You are responsible for ensuring that your submission is in valid format and that it will be readable and printable. Please double check your file before submitting it.
Paper Submission 2016-01 -15
Paper Decision Notification 2016-03-15
Camera-ready Submission 2016-04-15
Conference Days 2016-05-25 -- 2016-05-29