Training strong models starts with building strong datasets. In this talk, we’ll present a practical, end-to-end view of how data strategy drives model quality, development speed and iteration at scale. We’ll cover the core decisions in data collection—what to capture, […]

Depth sensing is a crucial technology for many applications, including robotics, automotive safety and biometrics. In this talk, we’ll provide an overview of depth-sensing technologies, including stereo vision, time-of-flight (ToF) and LiDAR. We will discuss the capabilities, trade-offs and limitations […]

Deep learning has transformed many aspects of computer vision, including object detection, enabling accurate and efficient identification of objects in images and videos. However, choosing the right deep neural network-based object detector for your project, particularly when deploying on lightweight […]

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: auto-exposure (AE), auto-focus (AF) and auto-white-balance (AWB). We’ll explain the core principles and logic behind each algorithm, […]

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 […]