Results 111 to 120 of about 204,781 (309)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

AAGCN: a graph convolutional neural network with adaptive feature and topology learning

Scientific Reports
In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power.
Bin Wang, Bodong Cai, Jinfang Sheng, Wenzhe Jiao   +3 more
doaj   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

Low Frequency Ultrasonic Voice Activity Detection using Convolutional Neural Networks [PDF]

Low frequency ultrasonic mouth state detection uses reflected audio chirps from the face in the region of the mouth to determine lip state, whether open, closed or partially open.
Song, Yan, McLoughlin, Ian Vince
core  

Electrically Coded Retinomorphic Spectrophotodetector

Advanced Materials, EarlyView.
Self‐powered retinomorphic pyro‐photodetector is demonstrated that avoids machine‐learning post‐processing and covers 365–940 nm. Electrostatic balancing of built‐in potential produces an electrical wavelength code, delivering <3 nm wavelength decoding accuracy with ∼46 µs response.
Mohit Kumar, Hyunmin Dang, Hyungtak Seo
wiley   +1 more source

Toward Audio Beehive Monitoring: Deep Learning vs. Standard Machine Learning in Classifying Beehive Audio Samples

Applied Sciences, 2018
Electronic beehive monitoring extracts critical information on colony behavior and phenology without invasive beehive inspections and transportation costs.
Vladimir Kulyukin, Sarbajit Mukherjee, Prakhar Amlathe   +2 more
doaj   +1 more source

Charge‐Encoded Sidechains Enable Deterministic Ion Ingress and Memory Retention in Organic Electrochemical Synaptic Transistors

Advanced Materials, EarlyView.
Organic electrochemical synaptic transistors based on sidechain‐engineered conjugated polyelectrolytes reveal that cationic sidechains enable efficient volumetric ion penetration and dense backbone doping, leading to enhanced transconductance and long‐term synaptic retention.
Haim Kwon, Jihyeon You, Chaeyeon Park, Dong Gue Roe, Ji Hyun Jung, Jeong Ho Cho, Han Young Woo   +6 more
wiley   +1 more source

At Home Detection of Ovarian Health Biomarker in Menstruation Blood

Advanced Materials Technologies, EarlyView.
A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon, Thomas Rduch, Salma Sherif Azer, Inge K. Herrmann   +3 more
wiley   +1 more source

Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment Using Convolutional Neural Networks

Journal of Alzheimer's Disease Reports
Background: Alzheimer’s disease and mild cognitive impairment are common diseases in the elderly, affecting more than 50 million people worldwide in 2020.
Sara Ghasemi Dakdareh, Karim Abbasian
doaj   +1 more source

A novel online ensemble convolutional neural networks for streaming data [PDF]

, 2019
In this study, we introduce an online ensemble method based on convolutional neural networks (CNNs) for streaming data. Recent work has shown that a convolution operation has been an effective way to extract features.
Pham, XC, Liew, AWC, Nguyen, TTT
core   +1 more source