Results 31 to 40 of about 534,506 (301)
ROLLING BEARING FAULT DIAGNOSIS BASED ON FUSION CNN AND PSO-SVM
Jixie qiangdu, 2021 Aiming at the problem that it is difficult to extract subtle fault features in the process of rolling bearing fault identification,this paper proposes a rolling bearing fault diagnosis method based on fusion convolutional neural network and support ...
WANG YongDing, JIN ZiQi
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Optical Diffractive Convolutional Neural Networks Implemented in an All-Optical Way
Sensors, 2023 Optical neural networks can effectively address hardware constraints and parallel computing efficiency issues inherent in electronic neural networks. However, the inability to implement convolutional neural networks at the all-optical level remains a ...
Yaze Yu +4 more
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Journal of Harbin University of Science and Technology, 2020 A method is proposed that the corresponding AlexNet neural network is trained according to the data of different flow patterns for the problem of slow sample training and low imaging accuracy for the threedimensional image reconstruction algorithm of ...
LI Yan, WANG Lu, LI Jiaqi
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Long Short-Term Memory Spatial Transformer Network
, 2019 Spatial transformer network has been used in a layered form in conjunction with a convolutional network to enable the model to transform data spatially.
Chen, Tianyue, Feng, Shiyang, Sun, Hao
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Miners' facial expression recognition method based on convolutional neural network
Gong-kuang zidonghua, 2018 In view of problems of low recognition rate and complex algorithm of traditional miner's facial expression recognition methods, based on convolutional neural network and combining with nonlinear mapping function in support vector machine algorithm, a ...
DU Yun, ZHANG Lulu, PAN Tao
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, 2017 Traditional recommendation systems rely on past usage data in order to generate new recommendations. Those approaches fail to generate sensible recommendations for new users and items into the system due to missing information about their past ...
A Rajaraman +4 more
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Algorithms, 2018 Variation in the format and classification requirements for remote sensing data makes establishing a standard remote sensing sample dataset difficult. As a result, few remote sensing deep neural network models have been widely accepted.
Wei Cui, Qi Zhou, Zhendong Zheng
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Test-object recognition in thermal images [PDF]
Компьютерная оптика, 2019 The paper presents a comparative analysis of several methods for recognition of test-object position in a thermal image when setting and testing characteristics of thermal image channels in an automated mode.
Aleksandr Mingalev +4 more
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Lithosphere, 2021 Average pore pressure in oil formation is an important parameter to measure energy in the formation and the capacity of injection–production. In past studies, average pore pressure mainly depends on pressure build-up test results, which have a high cost ...
Chaoyang Hu +4 more
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Learning to Detect Violent Videos using Convolutional Long Short-Term Memory
, 2017 Developing a technique for the automatic analysis of surveillance videos in order to identify the presence of violence is of broad interest. In this work, we propose a deep neural network for the purpose of recognizing violent videos.
Lanz, Oswald, Sudhakaran, Swathikiran
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