Coronavirus disease 2019(Covid-19)is a life-threatening infectious disease caused by a newly discovered strain of the *** by the end of 2020,Covid-19 is still not fully understood,but like other similar viruses,the ma...
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Coronavirus disease 2019(Covid-19)is a life-threatening infectious disease caused by a newly discovered strain of the *** by the end of 2020,Covid-19 is still not fully understood,but like other similar viruses,the main mode of transmission or spread is believed to be through droplets from coughs and sneezes of infected *** accurate detection of Covid-19 cases poses some questions to scientists and *** two main kinds of tests available for Covid-19 are viral tests,which tells you whether you are currently infected and antibody test,which tells if you had been infected ***-tine Covid-19 test can take up to 2 days to complete;in reducing chances of false negative results,serial testing is *** image processing by means of using Chest X-ray images and Computed Tomography(CT)can help radiologists detect the *** imaging approach can detect certain characteristic changes in the lung associated with *** this paper,a deep learning model or tech-nique based on the Convolutional Neural Network is proposed to improve the accuracy and precisely detect Covid-19 from Chest Xray scans by identifying structural abnormalities in scans or X-ray *** entire model proposed is categorized into three stages:dataset,data pre-processing andfinal stage being training and classification.
Given a multivariate quasi-interpolation operator with the partition of unity property,we propose a method to raise the accuracy with simple knots. The resulting operators possess higher accuracy while not requiring a...
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Given a multivariate quasi-interpolation operator with the partition of unity property,we propose a method to raise the accuracy with simple knots. The resulting operators possess higher accuracy while not requiring any derivative information of the underlying function. On that basis, we improve the multivariate spline quasi-interpolants with higher accuracy over type-2triangulations. Moreover, we apply the improved quasi-interpolants to simulate time developing partial differential equations(PDEs). The numerical experiments verify the efficiency of the proposed methods.
This study offers an improved YOLOv5s-based insulator defect identification method to solve the typical problems of missing and erroneous detections in insulator defect detection under complicated backgrounds. The fea...
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ISBN:
(数字)9798350375077
ISBN:
(纸本)9798350375084
This study offers an improved YOLOv5s-based insulator defect identification method to solve the typical problems of missing and erroneous detections in insulator defect detection under complicated backgrounds. The feature pyramid network now incorporates down-sampling channels, the CBAM attention mechanism is introduced, the CSPNet structure is optimized, and a dynamic weighted IoU loss function is implemented. Experimental results show that the improved YOLOv5s algorithm significantly outperforms the pre-optimization model in terms of accuracy, recall, and mAP in insulator defect detection. Specifically, the accuracy increased from 0.851 to 0.942, the recall from 0.804 to 0.931, mAP50 from 0.853 to 0.943, and mAP50-95 from 0.603 to 0.706. The improved algorithm demonstrates excellent performance in both detection accuracy and real-time capability, showing potential for practical application in U AV-based insulator defect inspections. This paper provides an effective technical means to enhance the efficiency and accuracy of power system inspections.
For the insufficient extraction of facial expression features by convolutional neural network VGG16, an improved VGG16-NFB network model is proposed to extract facial expression features more fully, so as to improve t...
For the insufficient extraction of facial expression features by convolutional neural network VGG16, an improved VGG16-NFB network model is proposed to extract facial expression features more fully, so as to improve the accuracy of facial expression recognition. Firstly, VGG16 is used to optimize the network structure, and the part before the classifier is used as the feature extractor to extract the features of facial expressions initially, and the redundant two full connection layers in the classifier are deleted. Then, a feature enhancement module FEM is designed, in which the representative batch normalization method can calibrate the feature information effectively, make the feature distribution more stable, and further enhance the network's ability to extract features from facial expressions. Finally, the global average pooling is used to extract the features of each level in the feature enhancement module, and the bridge attention module BAM is introduced to fuse the features of each level, which is used to generate attention weights to further enhance the facial expression features with high discrimination. The experimental results show that the improved VGG16-NFB network achieves 86.8% and 87.5% recognition accuracy on the RAF-DB and FERPlus facial expression datasets, respectively, which is 2.22% and 1.61% higher than the original network.
Bayesian sampling methods based on Hierarchical models Bayesian analysis methods are commonly used to estimate and infer the parameters of hierarchical models. In this paper, a sampling method based on the three-stage...
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Vocabulary is an important language skill that can affect a person's understanding of a sentence. Thus, lexical simplification is the task of converting difficult words into simpler words. It is to make it easier ...
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Distilling knowledge into generative models is a technique to extract knowledge from a large dataset and embed it into a generative model, which effectively reduces redeployment costs and boosts dataset distillation e...
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ISBN:
(数字)9798350355079
ISBN:
(纸本)9798350355086
Distilling knowledge into generative models is a technique to extract knowledge from a large dataset and embed it into a generative model, which effectively reduces redeployment costs and boosts dataset distillation efficiency. In this paper, we propose a novel approach to enhance the performance of generative models by expanding the size of the model pool. Our approach strives to improve the diversity of models in the model pool so that more distinctive information can be considered when matching the prediction logits. We also verified the proposed method is effective on the CIFAR-10 dataset.
With the gradual improvement of urbanization in China, it is important to research city branding to promote high-quality urban development. This paper uses CSSCI journals(including the expanded edition) in CNKI as the...
With the gradual improvement of urbanization in China, it is important to research city branding to promote high-quality urban development. This paper uses CSSCI journals(including the expanded edition) in CNKI as the data source to collect the papers related to city branding from 2001-2022, analyzes the research content of city branding based on the bibliometric method, and accordingly proposes strategies for city branding in Beijing. The analysis result shows that the research on city branding involves a wide range of content, mainly including city branding, place marketing, and multilayer brand strategy. Based on this, we propose strategic suggestions for city branding for Beijing: exploring the characteristics of city resources and enhancing the cultural connotation;building a multilayer brand strategy to promote regional development;expanding multi-channel marketing to highlight the differentiation of city brand.
The performances of preliminary test estimators for error variance based on W,LR and LM tests in a normal linear model are considered in this ***,the risks of the proposed estimators are derived and compared by theore...
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The performances of preliminary test estimators for error variance based on W,LR and LM tests in a normal linear model are considered in this ***,the risks of the proposed estimators are derived and compared by theoretical analysis and numerical calculation,*** results show that their risks are related to the equality constraint error and the critical value of ***,the minimum value of the risks can be achieved when the critical value of test equals to ***,the superiority conditions of the proposed estimators are ***,the results are illustrated by a simulation example.
Audio Deepfake Detection (ADD) aims to detect the fake audio generated by text-to-speech (TTS), voice conversion (VC) and replay, etc., which is an emerging topic. Traditionally we take the mono signal as input and fo...
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