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Explore dedicated audio processors for edge AI, improving user interfaces with lower latency and cost. Learn about voice integration challenges and design capabilities for effective implementation.
Comprehensive review of the inaugural tinyML EMEA Forum, highlighting key events, discussions, and future directions for the tinyML movement in Europe, Middle East, and Africa.
Explore ten essential principles for tinyML success, covering data engineering, codesign, metrics, reproducibility, and industry collaboration, to drive innovation in embedded machine learning.
Innovative approach using decision tree ensembles for energy-efficient ECG analysis, achieving high accuracy in detecting atrial fibrillation with minimal energy consumption.
Explore compact AI models without sacrificing quality. Learn to assess model quality, understand decision-making logic, evaluate training data, and interpret model outputs for tinyML applications.
Exploration des applications, avancées et défis du TinyML, mettant en lumière son potentiel dans les systèmes à très faible consommation et son impact sur l'IA embarquée et l'IoT.
Explore the journey of TinyML from face detection demos to large-scale commercial deployment in notebooks, addressing real-world challenges and bridging the gap between technology and business.
Explore ZigZag, a framework for optimizing deep learning accelerator design through architecture-mapping space exploration, enhancing efficiency in embedded systems.
Explore neuromorphic computing approaches for embedded cognition, comparing bottom-up and top-down designs through silicon implementations and discussing tradeoffs for edge computing applications.
Explore optimizing deep learning for edge devices through model efficiency techniques, including neural architecture search, pruning, quantization, and conditional processing.
Explore battery-free wireless smart cameras for face detection using edge AI and low-power microcontrollers. Learn about energy harvesting, tiny ML algorithms, and novel hardware architectures for IoT devices.
Explore Intel and Luxonis' DepthAI platform for advanced vision solutions. Learn about AI inference, OpenVINO toolkit, and developing spatial edge applications using the LUX-ESP32 device.
Explore building a TinyML-powered artificial nose, from concept to implementation. Learn about hardware, sensors, models, and integrating TinyML applications into IoT ecosystems.
Explore cutting-edge RISC-V multicore technology for image-based target identification, featuring GAP9 processor and innovative algorithms for advanced audio processing in hearable devices.
Explore bio-inspired neuromorphic circuits for ultra-low power, brain-like computing. Learn strategies for robust, low-latency processing using electronic neural elements, with applications in extreme-edge scenarios.
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