Visual AI is now central to many real-time and safety-critical embedded systems. In this introductory talk, we explain the foundation of how deep learning enables modern computer vision, starting with what images and video look like to a machine (tensors […]
Designing a camera system requires a deep understanding of the fundamental principles of image formation and the physical characteristics of its components. Translating computer vision-based system requirements into camera system parameters is a crucial step. In this talk, we will […]
In this session we’ll provide a comprehensive introduction to the three fundamental auto algorithms (3A) that enable high-quality imaging in embedded camera systems: autoexposure (AE), autofocus (AF) and auto white balance (AWB). We’ll explain the core principles and logic behind […]
Training a model is a crucial step in machine learning, but it can be overwhelming for beginners. In this talk, we provide a comprehensive introduction to the fundamentals of model training. We will introduce the different types of training, such […]
Unimodal vision systems are powerful but limited when users need flexible queries, richer semantics or reasoning that combines images/video with language. Vision-language models (VLMs) address this gap by jointly training visual and text encoders to align their representations, enabling tasks […]
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