In this presentation, we will provide an introduction to light detection and ranging (LiDAR) technology. We’ll explain how LiDAR sensors work and their main advantages and disadvantages. We’ll introduce different approaches to LiDAR, including scanning and flash LiDAR. We’ll explore […]
Selecting the appropriate type of image sensor is essential for reliable and accurate performance of vision applications. In this talk, we explore some of the critical factors to consider in selecting an image sensor, including shutter type, dynamic range, resolution […]
First-person or “egocentric” perception requires understanding the video and multimodal data that streams from wearable cameras and other sensors. The egocentric view offers a special window into the camera wearer’s attention, goals, and interactions with people and objects in the […]
Join us to hear about the new Hailo-15 AI vision processor family, specifically designed to empower smart cameras with unprecedented AI capabilities. In this talk, we’ll explain how the Hailo-15 family of processors—with performance ranging from 7 to 20 tera […]
The AIoT industry is expected to reach $1T by 2030—but that will happen only if edge devices rapidly become more intelligent. In this presentation, we’ll show how BrainChip’s Akida IP solution enables improved edge ML accuracy and on-device learning with […]
The phrase “garbage in, garbage out” is applicable to machine and human vision. If we can improve the quality of image data at the source by removing noise, this will have far-reaching impacts, such as improved accuracy later in the […]
The Qualcomm AI Stack revolutionizes how we think about AI software and provides the ultimate tool and user interface to enable our ecosystem partners to create faster and smarter AI applications for all embedded form factors. Focusing on real user […]
Being first to market can mean the difference between success and failure of a new product. But rapid product development brings challenges. With the growing use of AI in embedded vision applications, designers need more flexibility to change and refine […]
ImmersiView is a deep learning–based augmented reality solution for automotive safety. It uses a head-up display to draw a driver’s attention to important objects. The development of such solutions often resembles research more than development, with long development cycles and […]
Until recently, the majority of sensor-based AI processing used vision and speech inputs. Recently, we have begun to see radar, LiDAR, event-based image sensors and other types of sensors used in new AI applications. And, increasingly, system developers are incorporating […]
