Results 11 to 20 of about 7,124,551 (244)
Measuring Comfort Behaviours in Laying Hens Using Deep-Learning Tools
Animals, 2022 Image analysis using machine learning (ML) algorithms could provide a measure of animal welfare by measuring comfort behaviours and undesired behaviours.
Marco Sozzi +8 more
doaj +1 more source
MiCrowd: Vision-Based Deep Crowd Counting on MCU
Sensors, 2023 Microcontrollers (MCUs) have been deployed on numerous IoT devices due to their compact sizes and low costs. MCUs are capable of capturing sensor data and processing them. However, due to their low computational power, applications processing sensor data
Sungwook Son +5 more
doaj +1 more source
Machine learning for microalgae detection and utilization
Frontiers in Marine Science, 2022 Microalgae are essential parts of marine ecology, and they play a key role in species balance. Microalgae also have significant economic value. However, microalgae are too tiny, and there are many different kinds of microalgae in a single drop of ...
Hongwei Ning, Rui Li, Teng Zhou
doaj +1 more source
An 8-bit Single Perceptron Processing Unit for Tiny Machine Learning Applications
IEEE Access, 2023 We present a tiny MultiLayer Perceptron (MLP) accelerator named Single Perceptron Linear Vector Processor (SPLVP) that aims at extending the capabilities of limited resources MCUs, enabling inference time speedup and main CPU off-load.
Marco Crepaldi +2 more
doaj +1 more source
A review on TinyML: State-of-the-art and prospects
Journal of King Saud University: Computer and Information Sciences, 2022 Machine learning has become an indispensable part of the existing technological domain. Edge computing and Internet of Things (IoT) together presents a new opportunity to imply machine learning techniques at the resource constrained embedded devices at ...
Partha Pratim Ray
doaj +1 more source
Micromachines, 2022 Recently, the Internet of Things (IoT) has gained a lot of attention, since IoT devices are placed in various fields. Many of these devices are based on machine learning (ML) models, which render them intelligent and able to make decisions.
Norah N. Alajlan, Dina M. Ibrahim
doaj +1 more source
Tiny Machine Learning for Resource-Constrained Microcontrollers
, 2022 We use 250 billion microcontrollers daily in electronic devices that are capable of running machine learning models inside them. Unfortunately, most of these microcontrollers are highly constrained in terms of computational resources, such as memory ...
Immonen, Riku, Hämäläinen, Timo
core +1 more source
A Review of Causality for Learning Algorithms in Medical Image Analysis
, 2022 Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area.
Vlontzos, Athanasios +2 more
core +1 more source
Greedy structure learning from data that contain systematic missing values [PDF]
, 2022 Learning from data that contain missing values represents a common phenomenon in many domains. Relatively few Bayesian Network structure learning algorithms account for missing data, and those that do tend to rely on standard approaches that assume ...
Liu, Y +5 more
core +1 more source
DeepEdge: A Novel Appliance Identification Edge Platform for Data Gathering, Capturing and Labeling
Sensors, 2022 With the development of the Internet of Things for smart grid, the requirement for appliance monitoring has become an important topic. The first and most important step in appliance monitoring is to identify the type of appliance.
Zilin Wang +5 more
doaj +1 more source