Results 41 to 50 of about 4,069,375 (260)

NeuroVisio SyncPatch: A Skin‐Conformal Multimodal EMG–Motion Sensing Platform for Quantitative Neuromuscular Rehabilitation and Performance Monitoring

Advanced Healthcare Materials, EarlyView.
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi, Yoo‐Jin Jun, Heewon Choee, Kun‐Do Lee, Heesoo Kim, Yu Seok Hwang, Choong Yeon Kim, Seongok Chae, Juhyun Lee, Minkyu Je, Jae‐Woong Jeong, Hyung‐Soon Park   +11 more
wiley   +1 more source

Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model

Sensors, 2022
Walking is an exercise that uses muscles and joints of the human body and is essential for understanding body condition. Analyzing body movements through gait has been studied and applied in human identification, sports science, and medicine.
Jungi Kim, Haneol Seo, Muhammad Tahir Naseem, Chan-Su Lee   +3 more
doaj   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 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

A Survey on Graph Neural Networks for Microservice-Based Cloud Applications

Sensors, 2022
Graph neural networks (GNNs) have achieved great success in many research areas ranging from traffic to computer vision. With increased interest in cloud-native applications, GNNs are increasingly being investigated to address various challenges in ...
Hoa Xuan Nguyen, Shaoshu Zhu, Mingming Liu   +2 more
doaj   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network

Sensors, 2023
In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks ...
Dong Wang, Meiyan Lin, Xiaoxu Zhang, Yonghui Huang, Yan Zhu   +4 more
doaj   +1 more source

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

Canonical convolutional neural networks

, 2023
33983405We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical networks as scaled sums of outer vector products.
Wolter, Moritz, Klein, Reinhard, Veeramecheneni, Lokesh, Garcke, Jochen   +3 more
core   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source