Edge AI Insights | Edge AI and Vision Alliance

This collection covers advancements in edge artificial intelligence and computer vision technologies, focusing on on-device processing, model optimization for constrained environments, and the integration of AI in various applications such as robotics, automotive systems, and video analytics. Challenges such as cost, power consumption, and scaling are discussed alongside standards and frameworks aimed at enhancing AI deployment. Key themes include sensor fusion, multimodal capabilities, and the role of generative models in improving real-time processing and personalization.

“Toward Hardware-agnostic ADAS Implementations for Software-defined Vehicles,” a Presentation from Valeo

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“Object Detection Models: Balancing Speed, Accuracy and Efficiency,” a Presentation from Union.ai

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“Depth Estimation from Monocular Images Using Geometric Foundation Models,” a Presentation from Toyota Research Institute

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“Introduction to DNN Training: Fundamentals, Process and Best Practices,” a Presentation from Think Circuits

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“Introduction to Depth Sensing: Technologies, Trade-offs and Applications,” a Presentation from Think Circuits

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“Lessons Learned Building and Deploying a Weed-killing Robot,” a Presentation from Tensorfield Agriculture

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“Transformer Networks: How They Work and Why They Matter,” a Presentation from Synthpop AI

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“Understanding Human Activity from Visual Data,” a Presentation from Sportlogiq

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“Multimodal Enterprise-scale Applications in the Generative AI Era,” a Presentation from Skyworks Solutions

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“SKAIVISION: Transforming Automotive Dealerships with Computer Vision,” a Presentation from SKAIVISION

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“Real-world Deployment of Mobile Material Handling Robotics in the Supply Chain,” a Presentation from Pickle Robot Company

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“Developing a GStreamer-based Custom Camera System for Long-range Biometric Data Collection,” a Presentation from Oak Ridge National Laboratory

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“Scaling Artificial Intelligence and Computer Vision for Conservation,” a Presentation from The Nature Conservancy

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“A Lightweight Camera Stack for Edge AI,” a Presentation from Meta

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“Unlocking Visual Intelligence: Advanced Prompt Engineering for Vision-language Models,” a Presentation from LinkedIn Learning

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“Deploying Accelerated ML and AI: The Role of Khronos Open Standards,” a Presentation from the Khronos Group

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“Scaling Computer Vision at the Edge,” a Presentation from Invisible AI

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“Scaling Machine Learning with Containers: Lessons Learned,” a Presentation from Instrumental

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“Vision-language Models on the Edge,” a Presentation from Hugging Face

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“Vision LLMs in Multi-agent Collaborative Systems: Architecture and Integration,” a Presentation from Google

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