Cigdem Beyan

Foto Cigdem,  March 1, 2024
Position
Associate Professor
Academic sector
INF/01 - INFORMATICS
E-mail
cigdem|beyan*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page
https://cbeyan.github.io/

Modules

Modules running in the period selected: 2.
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Course Name Total credits Online Teacher credits Modules offered by this teacher
Master's degree in Computer Engineering for Robotics and Smart Industry Machine learning & artificial intelligence (2023/2024)   9  eLearning (Teoria)
PhD in Computer Science Multimodal Learning and Applications (2023/2024)   5   

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Research interests
Topic Description Research area
Image processing and computer vision Basic image processing, e.g. image enhancement, interpolation (digital zooming). Image processing applied to medical images, 2D and 3D segmentation, feature extraction, texture analysis. Optical flow extraction and processing. IMAGE PROCESSING AND COMPUTER VISION
Modellazione statistica di dati multimediali Modellazione di immagini e video, utilizzando strumenti statistici e probabilistici, quali modelli generativi (misture di Gaussiane, modelli di Markov a stati nascosti), discriminativi (Kernel Machines) ed embedding generativi, in spazi euclidei e non. Tale modellazione porta ad applicazioni come riconoscimento e rivelamento di oggetti, tracking, che si collocano nell'ambito della video sorveglianza, analisi di dati medicali e nell'analisi di segnali sociali o social signal processing. In particolare, le mie specialità attuali sono la re-identificazione e la detection per la sorveglianza, la segmentazione e classificazione per l'analisi di segnali medicali e l'analisi di attività interattive per il social signal processing. Machine Intelligence
Artificial intelligence
Video Surveillance and Monitoring This research aims at the analysis of people and the interpretation/recognition of human activities, possibly at the detection and prediction of events in unconstrained scenes, at individual, group and crowd level. In particular, the main target is on the analysis of nonverbal human behaviour, activities, and dialogue classification by considering vocal behavior, face & gazing, gesture & posture, space & environment. More specifically, the focus is on tracking and re-identification, object/person detection and classification, human pose estimation and activity recognition, automatic PTZ camera control, subjective surveillance, mobile sensing, data fusion. Machine Intelligence
Artificial intelligence



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