TinyML Journey: From Face Detection Demo to Real-Life Commercial Deployment
Exploring the journey from tinyML face detection demos to large-scale commercial deployment, addressing real-world challenges and bridging the gap between prototypes and practical applications.
tinyML: Impact and Growth of Always-On Devices
Explore the growing impact of tinyML devices in everyday life, from always-on voice in phones to environmental sensing in machines, and learn about the market's rapid expansion and technological requirements.
TinyML Vision Challenge - Summit 2021
Discover the tinyML Vision Challenge: Create innovative computer vision applications using tinyML, compete for $6k in prizes, and gain recognition from the tinyML Foundation.
Building a Magic Wand with TensorFlow Lite Micro - Tutorial
Learn to build an IMU-based gesture recognition model for Arduino, covering data gathering, training, and deployment using TensorFlow Lite Micro and CMSIS-NN library.
Powering the Next Generation of IoT with Embedded Machine Learning
Unlock IoT potential with Edge Impulse machine learning and Nordic's low-power wireless solutions. Learn to create motion detection, sound recognition, and image classification on edge devices using nRF52840 and nRF5340 kits.
Constraining 3D Fields for Reconstruction and View Synthesis
Explore advanced techniques in 3D field reconstruction and view synthesis, covering RegNeRF, MonoSDF, and TensoRF for improved neural rendering and geometric representation in computer vision.
AI at the Edge - Enabling Vision for Low-Power Devices
Explore AI's shift to edge devices, focusing on building efficient computer vision algorithms for battery-powered devices. Learn about data collection, continuous learning, and optimization techniques.
Accelerate Edge Compute with Syntiant's TinyML Platform
Explore Syntiant's TinyML platform for efficient edge AI in battery-powered devices, featuring Neural Decision Processors for enhanced processing and power efficiency compared to MCUs.
De-risking Embedded Machine Learning Projects Using Novel Technologies
Explore novel technologies for successful embedded machine learning projects, addressing challenges and ensuring customer success through innovative design and engineering philosophies.
Machine Learning at the Extreme Edge of Always-on Intelligent Sensor Networks
Explore ML optimization techniques for resource-constrained IoT sensor nodes, focusing on system, algorithm, architecture, and circuit levels to achieve significant area-power improvements.
TinyML Talks Morocco - Enabling Ultra-Low Power Always-On Computer Vision at Qualcomm
Exploring ultra-low power computer vision for TinyML applications, focusing on Qualcomm's innovations in sensors, hardware, and algorithms to enable always-on vision at 1mW power consumption.
Stable Diffusion DreamBooth Guide - Optimal Classification Images Count Comparison Test
Comprehensive guide on optimizing DreamBooth training in Automatic1111, comparing classification image counts for best results in AI image generation and fine-tuning.
Machine Learning and Earth System Modeling - From Parameter Calibration to Feature Detection
Explore machine learning applications in Earth system modeling, from parameter calibration to feature detection, enhancing climate predictions and understanding of complex environmental processes.
On the Neural Machinery of Faces
Explore the neural mechanisms behind face recognition, from visual processing to specialized face-selective cells, and their role in primate social cognition and intelligence.
Filters and Other Potions for Early Vision and Recognition
Explore early vision and recognition techniques, including filters, deep networks, and multiscale processing. Learn about spacetime oriented filters and tensor factorization for improved visual analysis.
Compositional Models - Complexity of Representation and Interference
Explore compositional models, their representation complexity, and interference effects. Delve into data-driven approaches, feedforward/feedback mechanisms, and hierarchical structures in generative modeling.
Transformations in Early Vision from a Symmetry Argument
Explore visual processing, machine vision, and V1 computations, delving into pinwheels, transfer functions, and edge detection filters in early vision transformations.
Social Visual Representations in Humans and Machines
Explore neural face representations, disentangled learning, and social interaction perception in vision, examining shared visual representations between humans and machines.
Why It Pays to Study Psychology - Lessons from Computer Vision
Explore how psychology insights enhance computer vision, from texture analysis to scene recognition and 3D reasoning. Learn about occlusion, visual memory, and self-supervised learning.
Automated Background Removal Using PyTorch - Wehkamp's Image Processing Pipeline
Discover an automated pipeline for efficient background removal in product images using PyTorch and machine learning, enhancing visual experiences for e-commerce customers.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.