Welcome to the Computational Intelligence Laboratory

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The Computational Intelligence Laboratory (CIL) is one of the six laboratories of the Institute of Informatics and Telecommunications which is part of the National Center for Scientific Research "DEMOKRITOS", the largest research center in applied sciences and engineering in Greece. CIL's main task is to undertake research and development activities in the area of intelligent and adaptive learning systems. CIL was founded in 2002 as a continuation of the former "Artificial Neural Networks Laboratory" which has been conducting research in selected strategic sectors of computational intelligence (neural networks and intelligent image processing) for more than a decade.

Core Research Activities

Machine Learning
Development of novel machine learning algorithms, especially concerning connectionist approaches and neural network architectures.

Pattern classification and recognition
Development of neural network based constrained learning algorithms for classification and object recognition. Also clustering algorithms with applications in several fields. A platform for solving pattern classification problems (Billnet) using connectionist and statistical methods has been developed by our group and is available on-line.

Knowledge representation
Development of decision support neural or knowledge based systems in many application areas, some of which are listed below. Feature selection and extraction methods for the efficient encoding of information.

Multimedia processing and retrieval
Experience and published work in the fields of segmentation, image understanding, optical character recognition, content-based image retrieval.

Core Projects

Document processing and understanding
Digital newspaper archive.
Automatic page analysis of old newspaper pages.
Advanced optical character recognition techniques.

Industrial Applications
Visual retrieval and classification of industrial parts
3D object recognition.

Web-based applications
Information retrieval from the Web using multimedia content for retail comparison.
Intelligent search engines for e-learning purposes.

Medical signal and image analysis
Intelligent processing of echocardiogram sequences.
Medical image segmentation.

Environmental applications
Information processing systems for: Land cover classification, geological feature extraction, water quality assessment.

Multimedia quality assessment
Video quality assessment.

Medical imaging software quality assessment

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