When converting floating-point networks to low-precision equivalents for high-performance inference, the primary objective is to maximally compress the network whilst maintaining fidelity to the original, floating-point network. This is made particularly challenging when only a reduced or unlabelled dataset is […]
Facilities and operations managers of buildings, college campuses, retail and foodservice establishments all struggle to answer one fundamental question: “What are people doing in our spaces?” Computer vision – specifically edge computer vision – provides the ability to not only […]
Recent advancements in machine learning have enabled market innovators to build insights from IoT sensors in the wild. These insights can be used to solve complex real-world challenges. The lack of security in typical vision-based IoT solutions is especially concerning, […]
We present the challenges and lessons learned in implementing a custom intelligent vision system to detect types of grain and measure flow rate and morphology of grains going through a milling system.
The traditional approach for in-cabin-monitoring uses cameras that capture only visible or near-infrared (NIR) light and are designed to represent a scene as closely as possible to what a human expects to see at a constant frame rate. But visible […]
Qualcomm has invested extensively in its state-of-the-art Qualcomm Neural Network and software stack, including the Qualcomm Neural Processing SDK and the AI Model Efficiency Toolkit. These toolkits have helped many developers take their applications to the next level with extreme […]
Every day, AI-enabled systems enhance how we live and work—and we’ve barely scratched the surface! These systems are poised to create new industries and dramatically improve the effectiveness, efficiency and safety of existing industries. In many cases, AI functionality will […]
In this talk, IoT industry pioneer and Edge Impulse co-founder Zach Shelby will share insights about how machine learning is revolutionizing embedded engineering. Advances in silicon and deep learning are enabling embedded machine learning (TinyML) to be deployed where data […]
Pattern recognition—such as that used in image recognition, speech recognition and machine translation—has been the primary focus of the last decade’s progress in artificial intelligence. But intelligence fundamentally requires more than mere pattern recognition: It also requires the ability to […]
