Artificial Neural Networks for IoT-Enabled Smart Applications

• Eará dahkkit: Velichko, Andrei (Doaimmaheaddji), Korzun, Dmitry (Doaimmaheaddji), Meigal, Alexander (Doaimmaheaddji)
• Materiálatiipa: Elektrovnnalaš Girjji oassi
• Giella: eaŋgalasgiella
• Almmustuhtton: MDPI - Multidisciplinary Digital Publishing Institute 2023
• Fáttát: Medicine; Neurosciences; deep learning; canine activity recognition; bark detection; wearable computing; search and rescue system; stacking; ensemble learning; distracted driving; imaginary speech; convolutional neural network; electroencephalography; signal processing; Kara One database; COVID-19; biochemical and hematological biomarkers; routine blood values; feature selection method; LogNNet neural network; Internet of Medical Things; IoT; 5G and beyond; child drowning prevention; network slicing architecture; point clouds; remote sensing; machine learning sensors; inertial measurement unit; smartphone; accelerometry; TUG test; gait; Parkinson's disease; "dry" immersion; arrhythmia; artificial intelligence (AI); cardiac; communication technologies; Electrocardiogram (ECG); systematic literature review (SLR); chemical carcinogens; machine learning; deep learning neural network; hybrid neural network; convolution neural network; fast forward neural network; edge computing; ANN; microprocessor; water level prediction; decentralized; n/a
• Liŋkkat: DOAB: download the publication; DOAB: description of the publication

In the age of neural networks and the Internet of Things (IoT), the search for new neural network architectures capable of operating on devices with limited computing power and small memory size is becoming an urgent agenda. This reprint focuses on recent developments in the organization of artifici...