About |
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Learning and NonLinear Models (ISSN 1676-2789) is the official journal of the Brazilian Society for Computational Intelligence (SBIC). LNLM has been published online since 2003 and all papers are Open-Access and indexed with DOI. The journal publishes papers reporting theoretical and practical advances in the several areas of Computational Intelligence. |
Call for Papers |
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Researchers are invited to submit high-quality papers and surveys with focus on the most recent advances in Deep Learning Methods. The scope of this special issue includes, but it is not limited to, the following topics: ● Methods: Convolutional Neural Networks, Convolutional Autoencoders, Recurrent Neural Networks, Long Short Term Memory Networks, Deep Belief Networks, Differentiable Neural Computer, Generative Adversarial Networks, Neural Turing Machines, Capsule Networks, Branch CNN, and other recent deep learning methods. ● Real-world applications of the above methods in: computer vision, signal processing, bioinformatics, novelty/anomaly detection, large-scale optimization, pattern recognition, big data/data analytics, engineering problems, intelligent manufacturing, and forecasting temporal series. |
Credits and Sources |
| [1] LNLM-SI-DL 2020 : Special Issue on Deep Learning Methods: Trends and Applications |
