The goal of TC14 is to promote interaction and collaboration among researchers working at the intersection of the disciplines of Signal Processing and Machine Intelligence. In the era of a society of information and knowledge, Machine Intelligence and Pattern Recognition have embraced a number of other research areas. Signal and Image Processing communities have a strong interest for developing fundamental theoretical “tools” which have been applied in a wide range of applications. Over the recent years, these two communities have acquired a strong interest on Machine Intelligence techniques and a substantial volume of work is taking place that combines tools from all these areas. Typical areas of interest are:

• Speech, audio and music applications.Image and video.

• Intelligent multimedia and web processing.

• Hidden Markov modeling.

• Kernel methods.

• Learning theory and modeling.

• Bayesian learning.

• Sequential learning.

• Neural networks learning.

• Feature generation and selection for signals and images (e.g., linear and non-linear PCA, ICA).

More specifically, the objectives of the IAPR-TC14 are:

• To facilitate establishing closer contacts among the researchers working in various directions within the areas of Signal Processing, Image and Video Processing , Machine Intelligence and Pattern Recognition.

• To create and maintain a membership list.

• To inform about forthcoming related conferences and workshops.

• To organize regularly workshops on Signal Analysis and Machine Intelligence.

One of the scopes of TC14 is to provide information and links about educational material useful to tutors and students in the fields of Pattern Recognition, Machine Intelligence, Signal and Image Processing. Such material can include a list of book titles, keynote papers, literature reviews and surveys, course materials, lecture notes and power point presentations. For any material to be included please contact Yiannis Kompatsiaris.