Offloading processing to accelerators enables embedded vision systems to process workloads that exceed the capabilities of CPUs. However, parallel processors adds complexity as workloads must be distributed and synchronized across processing resources. Proven open standard APIs and languages can significantly […]
Deep neural networks, widely used in computer vision tasks, require substantial computation and memory resources, making it challenging to run these models on resource-constrained devices. Quantization involves modifying DNNs to use smaller data types (e.g., switching from 32-bit floating-point values […]
In this presentation, we’ll explore how advanced image acquisition techniques reveal previously unseen information, improving the ability of algorithms to provide valuable insights. We will introduce various techniques, including high-resolution optics, filters, high dynamic range imaging and multispectral imaging. We’ll […]
In this session, we’ll outline the key steps required to implement a large language model (LLM) on a Raspberry Pi. We’ll begin by outlining the motivations for running LLMs on the edge and exploring practical use cases for LLMs at […]
Multimodal large language models represent a transformative breakthrough in artificial intelligence, blending the power of natural language processing with visual understanding. In this talk, we delve into the essence of these models. We begin by explaining how large language models […]
Running AI algorithms on battery-powered, low-cost devices requires a different approach to designing hardware and software. The power requirements are stringent at standby, but the device needs to be able to awaken quickly when an event is detected. The device […]
In this talk, we share highlights from our adventures developing computer vision solutions for the rail transportation industry. We begin with an introduction to the types of machine perception problems encountered in this unique industry. We then share insights gained […]
In this presentation we provide an introduction to radar (short for radio detection and ranging) for machine perception. Radar is a proven technology with a long history of successful development and it plays an increasingly important role in the deployment […]
In recent years there’s been tremendous focus on designing next-generation AI chipsets to improve neural network inference performance. As higher performance processors are called upon to execute ever-larger models—from vision transformers to LLMs—memory bandwidth is frequently the key performance bottleneck. […]
In this interview, Toly Kotlarsky of Zebra Technologies will discuss computer vision challenges and opportunities in grocery stores and other retail environments, especially in traditional checkout and self-checkout applications. He will highlight key challenges that have inhibited the use of […]
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