1. Image Information Mining - Organized by Daniela FAUR, Anamaria RĂDOI, and Corina VĂDUVA
There is an increasing interest in the analysis of Earth Observation (EO) and Multimedia images. Due to the technological development of the
acquisition systems, huge open access image archives have been lately formed. Image information mining tools focus on the possibility of extracting
the relevant information in an unsupervised manner or with a small input from the user.  The challenge appears due to the large number of
heterogeneous image sets that require a specific modeling and processing. In addition, the concept of learning is strictly connected to defining
specific use case scenarios that, in many cases, modifies the perspective from which the whole analysis system is conceived. The complexity of the
problem is moreover increased by the existence of the spatio-temporal diversity in both EO and video archives. In this sense, there is a constant
demand in the analysis and retrieval tools that are able to understand the information captured in these large data sets.

This special session aims at raising key scientific questions that need to be addressed in the context of image information mining, such as:
- Models and methods for extracting relevant information in multimedia and EO image;
- Automatic semantic interpretation of image content;
- Multi-temporal and multi-sensor diversity;
- Visualization tools;
- Dimensionality reduction;
- Knowledge discovery;
- Large datasets image retrieval;
- Machine Learning.

2. Chaos-Data Protection and Information Hiding in Communications - Organized by Safwan EL ASSAD, Adrian DIACONU
Security and privacy are important issues in any society, especially in the digital society. In any public communication network, such as satellite,
mobile-phone, and the Internet, it is almost impossible to prevent unauthorized people from eavesdropping. To make use of the already existed public
communication networks and to maintain the secrecy and privacy, cryptographic techniques are applied. In particular, chaos-based information hiding
and security have been widely used in the image and video systems.

The objective of this special session is to address the range of problems related to data protection and information hiding in public channels. We will
welcome papers both from theoretical and practical aspects. Prospective authors are invited to submit original, previously unpublished work, reporting
on novel and significant research contributions, on-going research projects, experimental results and recent developments related to, but not limited,
the following topics:
- Chaos-based Cryptography;
- Chaos-based Information Hiding and Security;
- Personal Cryptography Security;
- Cryptography;
- Data protection;
- Pseudo random number generation;
- Random number generation;
- Steganography;
- Watermarking;
- Security methods for communications;
- Data Integrity;
- Database Security and Privacy;
- E-business Security;
- Iteration Theory;
- Identification, Authentication and Non-repudiation;
- Intellectual Property Protection;
- Intrusion Detection & Prevention;
- Lightweight cryptography for green computing;
- Protocols for security
- Cryptanalysis;
- Standardization, etc.

3. Compressive Sensing and Applications - Organized by Daniela COLȚUC
“The theory of compressive sampling, also known as compressed sensing or CS is a novel sensing/sampling paradigm that goes against the common
wisdom in data acquisition” (Emmanuel Candes, IEEE Signal processing Magazine, March 2008).
CS - a theory that emerged ten years ago - asserts that one can recover certain signals and images from far fewer samples or measurements than
Shannon’s Sampling Theorem states. To make this possible, CS relies on two principles: sparsity, which pertains to the signals of interest, and
incoherence, which pertains to the sensing modality. The signal is sensed by random projection and recovered in a sparse representation space by l1
norm minimization. A large variety of numerical algorithm has been developed for CS, which is from the mathematical point of view a constrained
optimization problem.

CS is a very active research field. The research includes theoretical aspects like sparse representations, and sampling theory as well as a large
variety of applications. The applications range from cameras, medical imaging, radar technology and sensor networks to statistical learning. The
construction of CS based hardware is a great challenge. The concept of CS has inspired the development of new data acquisition hardware such as
single pixel camera. Products including CS are already on the market.

4. Sensors and Signal Processing for Space Applications - Organized by Dragoș SĂCĂLEANU, and Anca POPESCU
Space applications are some of the most challenging areas for hardware design and signal processing. New instruments, digital signal and image
processing techniques are being designed for radio, optical and other frequencies, advancing our understanding and defining new goals for
instrumentation and creating new paradigms. Signal processing in the context of sensor networks can provide important information in order to
optimize the applications used in everyday life. The main important issues to be addressed in every space application are therefore related to
Calibration, Imaging and Communication. In this context, the session addresses topics related to diverse types of sensors and instruments which can
be found in space applications.
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