Results 61 to 70 of about 42,190 (170)
A comparative study of machine learning models in predicting crop yield
Discover AgricultureThis paper explores different machine learning techniques applied in the prediction of crop yield based on meteorological parameters. Recurrent Neural Networks (RCN), Convolutional Neural Networks, Random Forest, Decision Trees, Gradient Boosting machine
Bobo Mafrebo Lionel +3 more
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Correction to: Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis. [PDF]
J Digit Imaging, 2021 Raja H +6 more
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HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image
CoRR, 2018 With the development of deep learning, the performance of hyperspectral image (HSI) classification has been greatly improved in recent years. The shortage of training samples has become a bottleneck for further improvement of performance. In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral ...
Yanan Luo +4 more
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Self-Supervised Voltage Sag Source Identification Method Based on CNN
Energies, 2019 A self-supervised voltage sag source identification method based on a convolution neural network is proposed in this study. In addition, a self-supervised CNN (Convolutional Neural Networks) voltage sag source identification model is constructed on the ...
Danqi Li +4 more
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Applied Sciences, 2019 Aiming at the problem of poor robustness of the intelligent diagnostic model, a fault diagnosis model of rolling bearing based on a multi-dimension input convolutional neural network (MDI-CNN) is proposed. Compared with the traditional convolution neural
Tao Zan +4 more
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Bankruptcy Analysis Using Images and Convolutional Neural Networks (CNN)
The marketing departments of financial institutions strive to craft products and services that cater to the diverse needs of businesses of all sizes. However, it is evident upon analysis that larger corporations often receive a more substantial portion of available funds. This disparity arises from the relative ease of assessing the risk of default and
Luiz Wanderley Tavares +3 more
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Food Image Recognition by Using Convolutional Neural Networks (CNNs)
CoRR, 2016 Food image recognition is one of the promising applications of visual object recognition in computer vision. In this study, a small-scale dataset consisting of 5822 images of ten categories and a five-layer CNN was constructed to recognize these images.
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An intrusion detection model based on convolution neural network for Internet of vehicles
Dianxin kexueIn order to improve the accuracy of detecting the cyber-attacks in Internet of vehicles, hyper-parameter optimization convolution neural network-based ensemble Intrusion detection system (CNES) was proposed.
ZHANG Rui
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Shock and VibrationDeep learning has recently received extensive attention in the field of rolling-bearing fault diagnosis owing to its powerful feature expression capability.
Baoquan Hu +3 more
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Research on Switching Current Model of GaN HEMT Based on Neural Network
MicromachinesThe switching characteristics of GaN HEMT devices exhibit a very complex dynamic nonlinear behavior and multi-physics coupling characteristics, and traditional switching current models based on physical mechanisms have significant limitations.
Xiang Wang +5 more
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