SoDeLIA 2017 : Special Session on Deep Learning and Its Applications

SoDeLIA: Special Session on Deep Learning and Its Applications


Deep Learning is a new exciting trend in machine learning that learns a hierarchical representation of input data without crafting the features explicitly. This enables an implementation of end-to-end generic machine learning algorithms. We encourage researchers to submit their unpublished papers in the following areas, but not limited to:

– Deep learning architectures: convolution neural networks, deep neural networks, deep belief networks, generative adversarial networks, recurrent neural networks, long-short-term memory, deep reinforcement learning, etc.

– Deep representation learning: deep structured learning, hierarchical learning, deep structured semantic annotations/models, etc.

– Applications of deep learning in computer vision, natural language processing, speech recognition, audio processing, etc.

– Applications of deep learning in creative industries: 3D modeling, games, graphic design, artistic style transfer, algorithmic music/text compositions, generative art, etc.

– Others: deep learning algorithms, parallel between deep learning and neuroscience, end-to-end learning, etc.

Important Dates for SoDeLIA


Paper submission deadline: 10 August 2017

Notification due: 22 August 2017

Camera ready paper and Registration due: 1 September 2017

Conference dates: 20-22 November 2017

SoDeLIA is part of MIWAI 2017. SoDeLIA accepts two categories of research and application papers:

Regular papers (8-14 pages, 20 mins oral presentation)

Short papers (6 pages, poster presentation or 20 mins oral presentation)

All accepted and presented papers will be included in the proceedings of MIWAI 2017 which will be published by Springer in LNAI, a topical subseries of LNCS focusing on artificial intelligence (Indexed in the ISI Conference Proceedings Citation Index, Scopus, EI Engineering Index, Google Scholar, DBLP, etc.)



Fast Track: Authors of best papers will be invited to submit extended versions (at least 30% of new content) of their work to be appreciated for publication in a Fast Track submission process of the Elsevier Applied Soft Computing (ASOC) Journal.

from CFPs on Artificial Intelligence : WikiCFP


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