Results 11 to 20 of about 42,190 (170)

Selective kernel networks for weakly supervised relation extraction

open access: yesCAAI 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
doaj   +1 more source

Controlled Cooling Temperature Prediction of Hot-Rolled Steel Plate Based on Multi-Scale Convolutional Neural Network

open access: yesMetals, 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
doaj   +1 more source

IoT-based intrusion detection system using convolution neural networks [PDF]

open access: yesPeerJ 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
doaj   +2 more sources

Research on Hierarchical Decomposition of Convolutional Neural Network [PDF]

open access: yesJisuanji 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
doaj   +1 more source

Hyperspectral Image Classification Using a Hybrid 3D-2D Convolutional Neural Networks

open access: yesIEEE 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
doaj   +1 more source

Facial Expression Recognition Using Hierarchical Features With Three-Channel Convolutional Neural Network

open access: yesIEEE 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
doaj   +1 more source

Implementation of Bartlett matched-field processing using interpretable complex convolutional neural network [PDF]

open access: yesJASA 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
doaj   +1 more source

Hyperspectral image classification of wolfberry with different geographical origins based on three-dimensional convolutional neural network

open access: yesInternational 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
doaj   +1 more source

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization [PDF]

open access: yesIEEE Transactions on Visualization and Computer Graphics, 2021
11 pages, 14 figures, to be presented at IEEE VIS 2020. For a demo video, see https://youtu.be/HnWIHWFbuUQ . For a live demo, visit https://poloclub.github.io/cnn-explainer/
Zijie J. Wang   +7 more
openaire   +3 more sources

Traffic sign recognition algorithm based on improved convolution neural network

open access: yes上海师范大学学报. 自然科学版, 2018
For the problem of low traffic sign recognition rate due to gradient diffusion in convolution neural network(CNN), an improved convolution neural network was proposed.
ZHU Yongjia, ZHANG Jing
doaj   +1 more source

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