Text Mining:

Research Themes:

  • Text categorization and clustering methods. We build algorithms and tools for the identification of stylistically homogeneous categories.
  • Writing style representation. We study the effectiveness of several features that capture stylistic properties of documents including low-level features like character n-grams and more elaborated features using the output of natural language processing tools.
  • Intelligent information retrieval. We are interested in measuring document similarity based on stylistic criteria and identifying parts of a single document with separate writing styles.

Applications:

  • Authorship attribution
  • Text and webpage genre detection
  • Plagiarism analysis

 

Data Mining:

Research Themes:

  • Bayesian networks: We emphasize on reasoning under conditions of uncertainty in complex, changing environments.
  • Text Mining: We endeavor to use ontologies with standard linear algebra and pattern recognition techniques to reveal significant text patterns.
  • Inforainment Data Mining: We focus on creating intelligent, interactive games and other entertaining environments by analysing user behavior during gameplay activity,.
  • Privacy-Preserving data mining: We focus on keeping sensitive information hidden from mining tasks without deteriorating the mining performance.
  • High-scale, parallel data mining: We emphasize on dealing with high-dimensionality problems in an effective and efficient manner.

 

Applications:

  • Modeling of intelligent sensor networks.
  • Modeling of multimedia databases in marketing applications.
  • Prediction of Financial Markets by incorporating stock indices with financial news.
  • Creation of artificial intelligence engines within action video games.
  • Privacy-Preserving Classification of horizontally and vertically partitioned datasets.
  • Nvidia CUDA based Radial Basis Function classification algorithm for large databases.

 

 

 

Image Processing and Computer Vision:

Research Themes:

  • Interactive Systems. We build tools appropriate to improve the image processing performance by using human feedback.
  • Historical Document Processing. We use intelligent systems in combination with classical document processing techniques intending to face common problems of historical in order to extract useful information from them.
  • Word Spotting. We investigate in the field of word spotting by the use of image matching techniques in order to face the failure of OCR and perform information retrieval in difficult cases of Document Images, e.g Historical Documents.
  • Binarization. We investigate in the field of Image Binarization Techniques. We have proposed appropriate techniques for Document Images. We have built appropriate database and we suggested objective ways for the evaluation of the binarization algorithms. We organized the IEEE ICFHR 2010 Contest: Quantitative Evaluation of Binarization Algorithms.

 

Applications:

 

  • Information Retrieval
  • Genealogical Tree
  • Image Segmentation
  • Image Cleaning and Enhancement
  • Algorithm Evaluation

 

Robotics:

Research Themes:

  • Navigation:We investigate the circulation of the robot through obdtacles by using 3d maps.
  • Sensors:We research the use of sensors on new applications.
  • AI:We apply AI techniques to robotic applications

Applications:

  • Pool cleaner
  • Robotic Head
  • Robotic Hand
  • Amphibian