Results 101 to 110 of about 848,733 (323)

Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage

Brain Sciences
Background: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing ...
Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man   +5 more
doaj   +1 more source

Development and Analysis of Artificial Neural Network Models for Rainfall Prediction by Using Time-Series Data [PDF]

, 2018
Neelam Mishra, Hemant Kumar Soni, Sanjiv Sharma, Arvind Kumar Upadhyay   +3 more
openalex   +1 more source

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

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source

Introducing a New Genetic Operator Based on Differential Evolution for the Effective Training of Neural Networks

Computers
Artificial neural networks are widely established models used to solve a variety of real-world problems in the fields of physics, chemistry, etc. These machine learning models contain a series of parameters that must be appropriately tuned by various ...
Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis   +2 more
doaj   +1 more source

Artificial intelligence used in genome analysis studies

The EuroBiotech Journal, 2018
Next Generation Sequencing (NGS) or deep sequencing technology enables parallel reading of multiple individual DNA fragments, thereby enabling the identification of millions of base pairs in several hours.
D’Agaro Edo
doaj   +1 more source

Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks [PDF]

, 2021
Karlo Leskovar, Denis Težak, Josip Mesec, Ranko Biondić   +3 more
openalex   +1 more source

Using artificial intelligence in routing schemes for wireless networks [PDF]

, 2007
For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation ...
Barbancho Concejero, Antonio, Barbancho Concejero, Julio, León de Mora, Carlos, Molina Cantero, Francisco Javier   +3 more
core  

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