TinyML Talks UK - Presenting the Upcoming Tiny Cookbook and the Next In-Person Activities
Explore TinyML with upcoming book insights and UK in-person activities. Learn about machine learning on microcontrollers and engage with experts in this exciting field.
How a Middle School Girl Solves a Real-Life Challenge Using TinyML - Gas Leak Detection
Discover how a 6th-grader built a gas leak detection device using tinyML, Wio Terminal, and Edge Impulse. Learn about the project's development, challenges, and future plans, plus insights on getting started with tinyML for young learners.
Exploring Techniques to Build Efficient and Robust TinyML Deployments
Explore techniques for efficient TinyML deployments, covering data challenges, quantization, and handling out-of-distribution data for robust edge AI applications.
Application of Ultra-Low-Power and Resource-Constrained Devices to Improve Health Care Delivery in Resource-Constrained Communities
Explore tinyML applications in healthcare, focusing on resource-constrained communities. Learn how ultra-low-power devices can improve diagnosis, monitoring, and logistics in challenging environments.
Lightweight Face Detection for Ultra-Low Power AI Processors - tinyML Asia 2021
Lightweight face detection method for ultra-low power AI processors, featuring real-time application and accuracy in various scenarios. Explores implementation on Himax WE-I Plus platform for always-on sensing products.
An Approach to Dynamically Integrate Heterogeneous AI Components in Multimodal User Authentication - tinyML Asia 2021
Approach to dynamically integrate heterogeneous AI components for multimodal user authentication, focusing on flexibility, performance, and energy efficiency in battery-powered devices.
Building and Enabling Voice Control with ARM Cortex-M
Explore Sensory's Edge-AI technology for creating custom wake words and voice control on ARM Cortex-M, with a focus on VoiceHub platform for developers.
TinyML4STEM - Using TinyML for Neuroscience in K12
Explore how tinyML and neuroscience combine to create engaging STEM education experiences for K-12 students, featuring insights from a successful pilot collaboration with Backyard Brains.
Evolutionary Needs of TinyML
Explore power-efficient AI solutions for battery-powered devices, focusing on ultra-low-power AI for always-on applications and discussing ongoing challenges in intelligent algorithm evolution.
Airborne Sound Maintenance in Remote Sites Using Low Power Federated Learning
Explore low-power federated learning for remote site maintenance using airborne sound, minimizing downtime and costs while adhering to GDPR regulations.
TinyML Talks Ukraine - Practical TinyML for Industrial Safety and Personnel Performance Monitoring
Practical implementation of TinyML for industrial safety and worker performance monitoring using custom hardware and TensorFlow Lite for motion recognition from IMU data.
Putting AI on a Diet: TinyML and Efficient Deep Learning
Efficient deep learning techniques for deploying AI on resource-constrained devices, including model compression, neural architecture search, and new design primitives for various applications.
Binarized Neural Networks on Microcontrollers
Explore Binarized Neural Networks for efficient deep learning on microcontrollers, enabling complex tasks with minimal memory and high performance using 1-bit encoding for weights and activations.
Embedded Machine Learning in the Real World
Explore embedded ML applications, challenges, and opportunities in real-world scenarios, focusing on tiny models, accelerated hardware, and practical tooling.
Acceleration of Deep Learning Inference on Raspberry Pi's VideoCore GPU
Explore techniques for accelerating deep learning inference on Raspberry Pi's VideoCore GPU, including optimized tools, libraries, and compilers for enhanced performance without compromising accuracy.
Tiny but Powerful: Hardware for High Performance, Low Power Machine Learning
Explore cutting-edge hardware for ultra-low power machine learning at the edge, covering TinyML applications, model optimization, and emerging trends in efficient computing.
How to Build Advanced Hand-Gestures Using Radar and TinyML
Explore advanced hand gesture control using radar and Edge AI for headphones, featuring a case study and development process with Imagimob AI software.
Building Products Using Edge AI - TinyML on MCUs
Explore building Edge AI products using Reality AI Tools 4.0. Learn to optimize sensor selection, minimize data collection costs, and generate explainable TinyML models for MCUs.
System Support for Efficient Multi-Resolution Visual Computing on Mobile Systems
Explores system support for efficient multi-resolution visual computing on mobile devices, discussing challenges and opportunities in OS and vision sensing pipeline architectures for dynamic workloads.
Practical Application of TinyML in Battery Powered Anomaly Sensors for Predictive Maintenance of Industrial Assets
Explore tinyML for industrial anomaly detection, enabling predictive maintenance through low-power sensors, wireless tech, and IoT cloud integration. Includes live demo and practical insights.
Recent Progress on TinyML Technologies and Always-On Machine Opportunities
Explore recent advancements in tinyML technologies, their implementation, and potential applications across various industries, with a focus on always-on machine learning for voice, vision, and sensing.