Results 61 to 70 of about 162,584 (247)

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

DECISION SYSTEM FOR STOCK DATA FORECASTING BASED ON HOPFIELD ARTIFICIAL NEURAL NETWORK

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2016
The paper describes a new method using Hopfield artificial neural network combined with technical analysis fractal analysis and feed-forward artificial neural networks for predicting share prices for a next day on a Stock Exchange.
Michał Paluch, Lidia Jackowska-Strumiłło   +1 more
doaj   +1 more source

Neural Network Implementation in Java

BizInfo, 2020
Artificial neural networks are a powerful tool that engineers can use in variety of purposes. The most common tasks are classification and regression, as well as control, modeling and prediction.
Nenad Jovanović, Bojan Vasović, Zoran Jovanović, Miloš Cvjetković   +3 more
doaj   +1 more source

On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks. [PDF]

PLoS ONE, 2013
A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems.
Paul Tonelli, Jean-Baptiste Mouret
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Alkali Ion‐Incorporated HfO2 Dielectrics for Reconfigurable Neuromorphic Computing

Advanced Functional Materials, EarlyView.
This work presents an indium gallium zinc oxide (IGZO) transistor with an alkali cation‐integrated hafnium dioxide (HfO2) dielectric exhibiting synaptic behavior via ion retention. The solution‐based film fabrication strategy overcomes the limitations of atomic layer deposition (ALD) and precursor coating, enabling the control of synaptic retention ...
Seung Yeon Ki, In Cheol Kwak, Seonkwon Kim, Jihyun Kim, Dong Gue Roe, Se‐Jin Kim, Joohoon Kang, Jeong Ho Cho   +7 more
wiley   +1 more source

Structure–Transport–Ion Retention Coupling for Enhanced Nonvolatile Artificial Synapses

Advanced Functional Materials, EarlyView.
Nitrogen incorporation into the conjugated backbone of donor–acceptor polymers enables efficient charge transfer and deep ion embedding in organic electrochemical synaptic transistors (OESTs). This molecular‐level design enhances non‐volatile synaptic properties, providing a new strategy for developing high‐performance and reliable neuromorphic devices.
Donghwa Lee, Jinsung Kim, Sein Chung, Junho Sung, Chaeyeon Han, Eunho Lee   +5 more
wiley   +1 more source

Harnessing Advanced Neural Architectures: A Comprehensive Approach to Stock Market Prediction Using ANN, BPNN, and GAN [PDF]

SHS Web of Conferences
The advent of advanced neural network models has revolutionized the field of machine learning, enabling breakthroughs in various domains such as computer vision, natural language processing, and predictive analytics.
Wang Yang
doaj   +1 more source

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

ANN Based Approach for Estimation of Construction Costs of Sports Fields

Complexity, 2018
Cost estimates are essential for the success of construction projects. Neural networks, as the tools of artificial intelligence, offer a significant potential in this field.
Michał Juszczyk, Agnieszka Leśniak, Krzysztof Zima   +2 more
doaj   +1 more source