In machine learning, we use data to automatically find dependencies in the world, with the goal of predicting future observations. Most machine learning methods build on statistics, but one can also try to go beyond this, assaying causal structures underlying statistical dependencies. It turns out that causality can play a central role in addressing some… Continue reading Symbolic, Statistical, and Causal Representations
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Digital Pathology: On the intersection of Computer Vision and Data Science
Due to the proliferation of whole-slide-imaging (WSI) digital scanners it is now possible to leverage computer vision, image analysis, and machine learning techniques, such as deep learning to process the digital pathology images in hopes to derive, diagnosis and prognosis markers. The convergence of digital imaging, data science and pathology gave rise to a new… Continue reading Digital Pathology: On the intersection of Computer Vision and Data Science
Hybrid AI for knowledge representation and model-based medical image understanding
Image understanding benefits from the modeling of knowledge about both the scene observed and the objects it contains as well as their relationships. We show in this context the contribution of hybrid artificial intelligence, combining different types of formalisms and methods, and combining knowledge with data. Knowledge representation may rely on symbolic and qualitative approaches,… Continue reading Hybrid AI for knowledge representation and model-based medical image understanding
Geometric deep learning
Unlock the world of Geometric Learning and Graph Convolutional Networks (GCNs) in this comprehensive course designed to empower you with cutting-edge knowledge and practical skills. Geometric learning is a fascinating field at the intersection of computer vision, machine learning, and data analysis, with applications ranging from image processing to 3D modeling and beyond.
Domain Adaptation and Generalization
There is an issue of domain shift in machine learning models, which occurs when models trained on one dataset perform poorly when tested on data from a different source. This problem is particularly relevant for visual models operating in the real world or when no labelled data is available for the target scenario. Domain adaptation… Continue reading Domain Adaptation and Generalization
Drone Vision for Infrastructure Inspection
This lecture overviews the use of drones for infrastructure inspection and maintenance. Various types of inspection, e.g., using visual cameras, LIDAR or thermal cameras are reviewed. Primary application area is electric line inspection. Line detection and tracking and drone perching are examined. Human action recognition and co-working assistance are overviewed.