Submissions should not exceed 12 pages in Springer LNCS format, and they will be accomplished through the easychair platform.
Accepted papers will be published as Springer LNCS proceedings. Please, consult the author information page for typesetting guidelines and templates. Usage of LaTeX2e is strongly recommended, using the llncs class. Please, note that contributions incorrectly formatted may delay publication process.
Call for special sessions
IWANN 2017 Special Sessions will be a very useful tool in order to complement the regular program with new and emerging topics of particular interest to the participating community. Special Sessions that emphasize multi-disciplinary and transversal aspects, as well as cutting-edge topics are especially encouraged and welcome.
Prospective organizers of special sessions should submit proposals indicating:
- Title of the proposed session.
- Motivation and objectives for the session, emphasizing the benefits for IWANN2017.
- Short biography of the organizer(s), a maximum of two (exceptionally, three), with complete address, and additional data for contact.
- List of, at least five (4 – 5) prospective contributed papers (including titles, authors, and contact information of the corresponding author/s).
Proposals are due before November 1st, 2016 and should be sent by e-mail, without specific format, to Daniel Rodríguez: email@example.com
Special session organizers should also contact a sufficient number of experts who are able to review the papers submitted to their session, bearing in mind that at least two reviews per paper are required in order to make the final assessment. The organizer of the special session may be one of these experts, or they may propose an alternative referee. The second mandatory referee will be chosen among the members of the IWANN2017 Program Committee.
Special Session organizers will benefit from a 24% reduction in registration fees.
The topics of interest include, but are not limited to:
- Mathematical and theoretical methods in computational intelligence. Mathematics for neural networks. RBF structures. Self-organizing networks and methods. Support vector machines and kernel methods. Fuzzy logic. Evolutionary and genetic algorithms.
- Neurocomputational formulations. Single-neuron modelling. Perceptual modelling. System-level neural modelling. Spiking neurons. Models of biological learning.
- Learning and adaptation. Adaptive systems. Imitation learning. Reconfigurable systems. Supervised, non-supervised, reinforcement and statistical algorithms.
- Emulation of cognitive functions. Decision Making. Multi-agent systems. Sensor mesh. Natural language. Pattern recognition. Perceptual and motor functions (visual, auditory, tactile, virtual reality, etc.). Robotics. Planning motor control.
- Bio-inspired systems and neuro-engineering. Embedded intelligent systems. Evolvable computing. Evolving hardware. Microelectronics for neural, fuzzy and bioinspired systems. Neural prostheses. Retinomorphic systems. Brain-computer interfaces (BCI) Nanosystems. Nanocognitive systems.
- Advanced topics in computational intelligence. Intelligent networks. Knowledge-intensive problem solving techniques. Multi-sensor data fusion using computational intelligence. Search and meta-heuristics. Soft Computing. Neuro-fuzzy systems. Neuro-evolutionary systems. Neuro-swarm. Hybridization with novel computing paradigms
- Applications. Expert Systems. Image and Signal Processing. Ambient intelligence. Biomimetic applications. System identification, process control, and manufacturing. Computational Biology and Bioinformatics. Parallel and Distributed Computing. Human Computer Interaction, Internet Modeling, Communication and Networking. Intelligent Systems in Education. Human-Robot Interaction. Multi-Agent Systems.