Results 21 to 30 of about 5,285,158 (212)
Audio Signal Extraction and Enhancement Based on CNN From Laser Speckles
IEEE Photonics Journal, 2022 A micro vibration signal extraction method based on deep neural network is proposed. Rough surface of vibrating object modulates the illuminating laser wave front and generates speckle pattern, which is recorded by a linear array CMOS and preprocessed ...
Chang Liu +4 more
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Selective kernel networks for weakly supervised relation extraction
CAAI Transactions on Intelligence Technology, 2021 The purpose of relation extraction is to identify the semantic relations between entities in sentences that contain two entities. Recently, many variants of the convolution neural network (CNN) have been introduced to relation extraction for the ...
Ziyang Li +4 more
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Metals, 2022 Controlled cooling technology is widely used in hot-rolled steel plate production lines. The final cooling temperature directly affects the microstructure and properties of steel plates, but cooling and heat transfer constitutes a nonlinear process ...
Xiao Hu +3 more
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IoT-based intrusion detection system using convolution neural networks [PDF]
PeerJ Computer Science, 2021 In the Information and Communication Technology age, connected objects generate massive amounts of data traffic, which enables data analysis to uncover previously hidden trends and detect unusual network-load.
Abdullah Aljumah
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Research on Hierarchical Decomposition of Convolutional Neural Network [PDF]
Jisuanji gongcheng, 2019 With the continuous development of deep learning,Convolutional Neural Network(CNN) have received extensive attention from researchers in target detection and image classification.CNN have evolved from LeNet-5 networks to deep residual networks,and the ...
KE Yan, LIN Xiaozhu, LIAO Rui, WEI Zhanhong
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Hyperspectral Image Classification Using a Hybrid 3D-2D Convolutional Neural Networks
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Due to the unique feature of the three-dimensional convolution neural network, it is used in image classification. There are some problems such as noise, lack of labeled samples, the tendency to overfitting, a lack of extraction of spectral and spatial ...
Saeed Ghaderizadeh +4 more
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IEEE Access, 2023 Aiming at the problem of insufficient feature extraction and low recognition rate of traditional convolutional neural network in facial expression recognition, a multi-layer feature recognition algorithm based on three-channel convolutional neural ...
Ying He +3 more
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Implementation of Bartlett matched-field processing using interpretable complex convolutional neural network [PDF]
JASA Express Letters, 2023 Neural networks have been applied to underwater source localization and achieved better performance than the conventional matched-field processing (MFP). However, compared with MFP, the neural networks lack physical interpretability.
Mingda Liu, Haiqiang Niu, Zhenglin Li
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International Journal of Food Properties, 2021 The hyperspectral image is a three-dimensional (3D) hypercube with spectral and spatial continuity. Traditional hyperspectral imaging (HSI) processing mainly focuses on spectral information.
Qingshuang Mu +5 more
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Lixdh12/Hand-Gesture-Recognition-Using-Background-Elllimination-and-Convolution-Neural-Network:
, 2021 Hand Gesture Recognition using Convolution Neural Network built using Tensorflow, OpenCV and ...
Sparsha Saha, mohammed-Emad
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