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This course examines the processes of geological hazards and how they impact on society, with some attention given to techniques and strategies for hazard mitigation. It covers earthquakes, volcanic eruptions, liquefaction, rockfall, and flooding.
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The course gives a broad overview of the archaeology, history, and art history of the material culture and of the written sources from the eighth to the twelfth centuries. The course covers different aspects of the political, social, cultural, and religious developments, as well as changes within Scandinavia. This includes such aspects as the transition from paganism to Christianity, Viking Age burials, gender and social segregation, trade and plundering, rural and urban landscapes, and economic development.
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This course is part of the Laurea Magistrale program. The course is intended for advanced level students only. Enrollment is by consent of the instructor. At the end of the course students know the basic principles of computer vision and image processing algorithms. Thus, they are able to understand and apply a variety of algorithms and operators aimed at either extracting relevant semantic information from digital images or improving image quality. They also understand the diverse challenges and design choices characterizing the main applications and acquire familiarity with software tools widely adopted in these scenarios. Course topics: Basic definitions related to image processing and computer vision–an overview across major application domains: Image Formation and Acquisition–geometry of image formation, pinhole camera and perspective projection, geometry of stereopsis, using lenses, field of view and depth of field, projective coordinates and perspective projection matrix; Camera calibration: intrinsic and extrinsic parameters, lens distortion, camera calibration based on planar targets and homography estimation (Zhang's algorithm); Image rectification and stereo calibration, basic notions on image sensing, sampling, and quantization; Intensity Transformations–image histogram, linear and non-linear contrast stretching, histogram equalization; Spatial Filtering– linear shift-invariant operators, convolution, and correlation; mean and Gaussian filtering, median filtering, bilateral filtering, non-local means; Image Segmentation–binarization by global thresholding, automatic threshold estimation, spatially adaptive binarization, color-based segmentation; Binary Morphology–dilation and erosion, opening and closing- hit-and-miss; Blob Analysis–distances on the image plane and connectivity, labeling of connected components, basic descriptors: area, perimeter, compactness, circularity, orientation and bounding-box, form factor and related descriptors, Euler number, image moments, invariant moments; Edge Detection–image gradient. smooth derivatives: Prewitt, Sobel, Frei-Chen, non-maxima suppression, Laplacian of Gaussion, canny edge detector; Local Invariant Features–detectors and descriptors, Harris Corners, scale invariant features, SIFT features, efficient feature matching by kd-trees; Object Detection–pattern matching by SSD, SAD, NCC and ZNCC, fast pattern matching, shape-based matching, Hough Transform for analytic shapes, Generalized Hough Transform, object detection by local invariant features, Hough-based voting, least-squares similarity estimation. The theoretical part of the course is complemented with assisted hands-on lab sessions based on Python and the OpenCV library. Lab sessions cover selected topics such as intensity transformations, spatial filtering, camera calibration, motion estimation and local invariant features.
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COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
This course deepens students’ knowledge of the “collective action dilemma” from a social science perspective and acquaints them with two interdependent global problems: climate change and energy. It analyzes and discusses possible political solutions to the management of climate and energy issues as well as dilemmas over natural resources at the local, regional, and international levels.
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COURSE DETAIL
This course introduces theoretical approaches and methodological tools to analyze the role of the European Union as a global actor across policy areas and over time. It investigates the legal, political, and economic determinants of European Union "actorness" in domains such as trade, environmental protection, promotion of human rights, and civilian and military assistance. Considering the current geopolitical context, the course discusses the extent to which the war in Ukraine shapes EU foreign policy. It identifies the main conceptualizations of the European Union as a power and the main actors involved in EU foreign policy, and covers the central features of the Common Foreign and Security Policy (CFSP) and the Common Security and Defense Policy (CSDP). The course includes an opportunity to analyze a case study concerning EU external action using the theoretical and methodological elements seen in class.
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