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Computer vision is a research area that studies how to make computers efficiently perceive, process, and understand visual data such as images and videos. It has important applications in areas such as healthcare, face recognition, industrial robotics, or autonomous driving. Modern machine learning methods such as deep neural networks have recently led to substantial progress in the field, pushing the performance of computer vision systems close to human-level performance on certain tasks.
The lecture starts with an overview of deep neural networks. It then discusses design principles of deep neural network architectures for computer vision problems. Specific computer vision problems such as image classification, segmentation,object detection and localization, or metric learning are discussed. The lecture also presents examples for practical applications of computer vision techniques in different domains.
The lecture starts with an overview of deep neural networks. It then discusses design principles of deep neural network architectures for computer vision problems. Specific computer vision problems such as image classification, segmentation,object detection and localization, or metric learning are discussed. The lecture also presents examples for practical applications of computer vision techniques in different domains.
Category: Informatik