Results 101 to 110 of about 2,288,742 (339)

Artificial Neural Network: Understanding the Basic Concepts without Mathematics

Dementia and Neurocognitive Disorders, 2018
Machine learning is where a machine (i.e., computer) determines for itself how input data is processed and predicts outcomes when provided with new data. An artificial neural network is a machine learning algorithm based on the concept of a human neuron.
Su-Hyun Han, K. Kim, Sangyun Kim, Y. Youn   +3 more
semanticscholar   +1 more source

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source

Automatic Driver Drowsiness Detection Using Artificial Neural Network Based on Visual Facial Descriptors: Pilot Study

Nature and Science of Sleep, 2022
Papangkorn Inkeaw,1 Pimwarat Srikummoon,2,3 Jeerayut Chaijaruwanich,1,4 Patrinee Traisathit,2,3,5 Suphakit Awiphan,1,4 Juthamas Inchai,6 Ratirat Worasuthaneewan,7 Theerakorn Theerakittikul6,7 1Data Science Research Center, Department of Computer Science,
Inkeaw P, Srikummoon P, Chaijaruwanich J, Traisathit P, Awiphan S, Inchai J, Worasuthaneewan R, Theerakittikul T   +7 more
doaj  

Crack‐Growing Interlayer Design for Deep Crack Propagation and Ultrahigh Sensitivity Strain Sensing

Advanced Functional Materials, EarlyView.
A crack‐growing semi‐cured polyimide interlayer enabling deep cracks for ultrahigh sensitivity in low‐strain regimes is presented. The sensor achieves a gauge factor of 100 000 at 2% strain and detects subtle deformations such as nasal breathing, highlighting potential for minimally obstructive biomedical and micromechanical sensing applications ...
Minho Kim, Taewi Kim, Jieun Park, Insic Hong, Myungrae Hong, Seonggyeong Park, Beomjin Kim, Sehyuk Ahn, Siwoo Jang, Seungyong Han, Je‐Sung Koh, Daeshik Kang   +11 more
wiley   +1 more source

Practical Approach to Studying Evolutionary Methods for Setting Weight Coefficients of Artificial Neural Networks

Цифровая трансформация
The article describes the problems of developing neurocontrollers for controlling dynamic objects, including the complexity of forming training data sets. It is indicated that one of the known methods for training an artificial neural network controlling
D. O. Petrov
doaj   +1 more source

Energy Efficiency Prediction using Artificial Neural Network [PDF]

, 2019
Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important,
Abu-Naser, Samy S., Abu-Nasser, Bassem S., Barhoom, Alaa M., Khalil, Ahmed J., Musleh, Musleh M.   +4 more
core  

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

Advanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao, Che Liu, Jia Cheng Li, Zhen Hao Fu, Yi Su Huang, Si Qi Huang, Lei Zhang, Jian Wei You, Tie Jun Cui   +8 more
wiley   +1 more source

An application and modelling on the artificial neural network to the RHV Tube [PDF]

Revista Română de Informatică și Automatică
Artificial neural networks represent highly advanced and adaptable tools for addressing challenges, attributed to their capacity for learning through examples and forming generalisations.
Murat Eray KORKMAZ
doaj   +1 more source

Measuring context dependency in birdsong using artificial neural networks [PDF]

, 2020
Takashi Morita, Hiroki Koda, Kazuo Okanoya, Ryosuke O. Tachibana   +3 more
openalex   +1 more source

Artificial Neural Network Pruning to Extract Knowledge

, 2020
Artificial Neural Networks (NN) are widely used for solving complex problems from medical diagnostics to face recognition. Despite notable successes, the main disadvantages of NN are also well known: the risk of overfitting, lack of explainability ...
Mirkes, Evgeny M
core