Software

“Computer Vision at Sea: Automated Fish Tracking for Sustainable Fishing,” a Presentation from Tryolabs and the Nature Conservancy

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Alicia Schandy Wood, Machine Learning Engineer at Tryolabs, and Vienna Saccomanno, Senior Scientist at The Nature Conservancy, co-present the “Computer Vision at Sea: Automated Fish Tracking for Sustainable Fishing” tutorial at the May 2025 Embedded Vision Summit. What occurs between the moment a commercial fishing vessel departs from shore and… “Computer Vision at Sea: Automated […]

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Simplifying Vision AI Development with Renesas AI Model Deployer Powered by NVIDIA TAO

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This blog post was originally published at Renesas’ website. It is reprinted here with the permission of Renesas. Edge AI is no longer a futuristic idea—it’s an essential technology driving today’s smart devices across industries, from industrial automation to consumer IoT applications. But building AI applications at the edge still comes with challenges: complexity with

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“Squinting Vision Pipelines: Detecting and Correcting Errors in Vision Models at Runtime,” a Presentation from Squint AI

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Ken Wenger, Chief Technology Officer at Squint AI, presents the “Squinting Vision Pipelines: Detecting and Correcting Errors in Vision Models at Runtime” tutorial at the May 2025 Embedded Vision Summit. As humans, when we look at a scene our first impressions are sometimes wrong; we need to take a second… “Squinting Vision Pipelines: Detecting and

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The Outer Loop: The Real Driver of AI Success

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This blog post was originally published in expanded form at RapidFire AI’s website. It is reprinted here with the permission of RapidFire AI. When people talk about deep learning, they usually talk about the inner loop—the elegant dance of forward passes, backpropagation, and gradient descent. This is the part that’s been endlessly refined over the

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“ONNX and Python to C++: State-of-the-art Graph Compilation,” a Presentation from Quadric

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Nigel Drego, Co-founder and Chief Technology Officer at Quadric, presents the “ONNX and Python to C++: State-of-the-art Graph Compilation” tutorial at the May 2025 Embedded Vision Summit. Quadric’s Chimera general-purpose neural processor executes complete AI/ML graphs—all layers, including pre- and post-processing functions traditionally run on separate DSP processors. To enable… “ONNX and Python to C++:

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Low-power Computer Vision Challenge: Empowering AI Development on Edge Devices

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. The Low-Power Computer Vision Challenge (LPCVC) is an annual competition organized by the Institute of Electrical and Electronics Engineers (IEEE) to improve the energy efficiency of computer vision technologies for systems with constrained resources. Established in 2015

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“Beyond the Demo: Turning Computer Vision Prototypes into Scalable, Cost-effective Solutions,” a Presentation from Plainsight Technologies

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Kit Merker, CEO of Plainsight Technologies, presents the “Beyond the Demo: Turning Computer Vision Prototypes into Scalable, Cost-effective Solutions” tutorial at the May 2025 Embedded Vision Summit. Many computer vision projects reach proof of concept but stall before production due to high costs, deployment challenges and infrastructure complexity. This presentation… “Beyond the Demo: Turning Computer

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“Running Accelerated CNNs on Low-power Microcontrollers Using Arm Ethos-U55, TensorFlow and Numpy,” a Presentation from OpenMV

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Kwabena Agyeman, President of OpenMV, presents the “Running Accelerated CNNs on Low-power Microcontrollers Using Arm Ethos-U55, TensorFlow and Numpy” tutorial at the May 2025 Embedded Vision Summit. In this presentation, Agyeman introduces the OpenMV AE3 and OpenMV N6 low-power, high-performance embedded machine vision cameras, which are 200x better than the… “Running Accelerated CNNs on Low-power

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R²D²: Building AI-based 3D Robot Perception and Mapping with NVIDIA Research

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This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Robots must perceive and interpret their 3D environments to act safely and effectively. This is especially critical for tasks such as autonomous navigation, object manipulation, and teleoperation in unstructured or unfamiliar spaces. Advances in robotic perception increasingly

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Unlocking the Power of Edge AI With Microchip Technology

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This blog post was originally published at Microchip Technology’s website. It is reprinted here with the permission of Microchip Technology. From the factory floor to the operating room, edge AI is changing everything. Here’s how Microchip is helping developers bring real-time intelligence to the world’s most power-constrained devices. Not long ago, Artificial Intelligence (AI) lived

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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