The international Image Processing Applications and Systems conference is intended for grouping from all over the world challenging researchers, innovators, academicians, and practitioners in image processing theory and tools, for following high level tutorials, sharing their achievements, exchanging their experiences and discussing future orientations. The conference will also offer an opportunity to make a bridge between image processing researchers and people working in other application fields such as medical doctors, radiotherapists or industrial parts. Accepted and registred papers will be submitted to be published in IEEE Explore. Special attention will be devoted to image processing algorithms and the way to implement these algorithms for best performances. Hardware implementations on embedded platforms are of particular interest. Five main topics will be treated:
1. Image and Video Processing Theory (IVPT)
2. Image and Video Processing Applications (IVPA)
3. Computer Science and Imaging (CSI)
4. Real Time Image Processing (RTIP)
5. Human Focused Analysis (HFA)
Papers describing general surveys, image processing fundamental theory, specific medical imaging applications, advanced prototypes, tools and methodologies are welcomed. Extended papers describing original contributions are encouraged in the Conference topics mentioned above.
Full paper submission: April 15th, 2016,
Acceptance notification: May 1st, 2016,
Final paper submission: May 15th, 2016
Tutorials will be held on the first day. Proposals for tutorials must include a title, an outline of the tutorial and its motivation, a two-page C.V. of the presenter(s), and a short description of the material to be covered. Proposals for tutorials should be submitted to firstname.lastname@example.org by March 15th, 2016.
Lectures will be focussed on specific areas, describing up-to-date theoretical advances, recent research axis, challenging or innovating contributions, covering the above mentioned topics.
Special sessions are encouraged in the following thematics: Inverse Problems and Sparse modelling in Imaging Science, Deterministic regularization and Bayesian Solutions, Data reduction and Component Analysis beyond classical PCA and ICA, Supervised and Unsupervised Classification: Beyound classical LDA, QDA, GMM and naive Bayes