Results 71 to 80 of about 1,429,068 (340)
Irregular Convolutional Neural Networks [PDF]
2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017 7 pages, 5 figures, 3 ...
Jiabin Ma, Wei Wang, Liang Wang
openaire +2 more sources
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
Italian National Conference on Sensors, 2016 Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor ...
Francisco Javier Ordonez, D. Roggen
semanticscholar +1 more source
Autonomous Control of Extrusion Bioprinting Using Convolutional Neural Networks
Advanced Functional Materials, EarlyView.This work presents a novel computer vision system for high‐fidelity monitoring of extrusion‐based bioprinting and a correction system utilizing convolutional neural networks for error mitigation. This system has demonstrated high detection accuracy and extrusion correction abilities that advance the state of the art toward accelerated printing ...
Daniel Kelly +4 more
wiley +1 more source
Phylogenetic convolutional neural networks in metagenomics [PDF]
BMC Bioinformatics, 2018 Presented at BMTL 2017 ...
Claudio Agostinelli +7 more
openaire +7 more sources
Advanced Functional Materials, EarlyView.This study introduces a paper‐based biodegradable, humidity‐insensitive e‐nose for real‐time breath analysis, addressing challenges in existing technologies such as humidity interference, high costs, and environmental impact. Featuring hydrophobic polymer coatings, these sensors reliably detect VOCs even in high‐moisture environments.
Indrajit Mondal +2 more
wiley +1 more source
Automatic Approach for Brain Aneurysm Detection Using Convolutional Neural Networks
Applied Sciences, 2023 The paper introduces an approach for detecting brain aneurysms, a critical medical condition, by utilizing a combination of 3D convolutional neural networks (3DCNNs) and Convolutional Long Short-Term Memory (ConvLSTM).
Martin Paralic +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Heterojunctions combining halide perovskites with low‐dimensional materials enhance optoelectronic devices by enabling precise charge control and improving efficiency, stability, and speed. These synergies advance flexible electronics, wearable sensors, and neuromorphic computing, mimicking biological vision for real‐time image analysis and intelligent
Yu‐Jin Du +11 more
wiley +1 more source
Advanced Functional Materials, EarlyView.This study presents a novel method using laser‐induced graphene (LIG) to enable high‐yield transfer of silver nanowire (AgNW) networks onto ultra‐low modulus, breathable silicone substrates. This approach creates ultra‐conformal epidermal electrodes (≈50 µm) for long‐term, high‐fidelity electrophysiological monitoring, even in challenging conditions ...
Jiuqiang Li +10 more
wiley +1 more source
FocusedDropout for Convolutional Neural Network
Applied Sciences, 2022 In a convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except for randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units.
Minghui Liu +6 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu +6 more
wiley +1 more source