Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of ***,there is a large performance gap between weakly supervised and fully supervised salient o...
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Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of ***,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background ***,an intuitive idea is to infer annotations that cover more complete object and background regions for *** this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent ***,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster ***,the same annotations for pixels with similar colours within each kernel neighbourhood was set *** experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.
Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanis...
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Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price ***,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock *** discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock ***,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation *** results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.
1 Introduction The Internet of Things(IoT)has facilitated the development of numerous fields in our ***,some equipment in IoT environment lacks sufficient storage and data processing capabilities[1].A feasible strateg...
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1 Introduction The Internet of Things(IoT)has facilitated the development of numerous fields in our ***,some equipment in IoT environment lacks sufficient storage and data processing capabilities[1].A feasible strategy is to leverage the powerful computing capabilities of cloud servers to process the data within the IoT devices.
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar...
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Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.
As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical im...
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As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical images such as magnetic resonance imaging(MRI),computed tomography(CT),these models do not model the relevance of images in vertical space,resulting in poor accurate analysis of consecutive slices of the same *** the other hand,the large amount of detail lost during the encoding process makes these models incapable of segmenting small-scale tumor *** at the scene of small-scale target segmentation in 3D medical images,a fully new neural network model SUNet++is proposed on the basis of UNet and UNet++.SUNet++improves the existing models mainly in three aspects:1)the modeling strategy of slice superposition is used to thoroughly excavate the three dimensional information of the data;2)by adding an attention mechanism during the decoding process,small scale targets in the picture are retained and amplified;3)in the up-sampling process,the transposed convolution operation is used to further enhance the effect of the *** order to verify the effect of the model,we collected and produced a dataset of hyperintensity MRI liver-stage images containing over 400 cases of liver *** results on both public and proprietary datasets demonstrate the superiority of SUNet++in small-scale target segmentation of three-dimensional medical images.
As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management *** has become a promi...
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As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management *** has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and ***,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial *** examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong ***,the security of AI models for the digital communication signals identification is the premise of its efficient and credible *** this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial *** we present more detailed adversarial indicators to evaluate attack and defense ***,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.
Epoxy resin(EP),as a resin material with excellent insulation performance,has been widely applied in fields such as electronics,coatings,ships ***,epoxy resins generally have poor thermal conductivity,which limits the...
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Epoxy resin(EP),as a resin material with excellent insulation performance,has been widely applied in fields such as electronics,coatings,ships ***,epoxy resins generally have poor thermal conductivity,which limits their application in the field of new generation of electronic *** address the key issues mentioned above,the BN@Fe_(3)O_(4)particles with positive out-of-plane thermal conductivity were successfully prepared in this study,having a core-shell structure with rough surfaces as *** a thermal conductive powder,the disadvantage of hexagonal boron nitride being easily agglomerated in resin has been *** applying an external magnetic field,three-dimensional thermal conduction pathways were constructed in the *** physical and chemical properties of the BN@Fe_(3)O_(4)powder and its composite materials were analysed and *** experiment indicates that the thermal conductive magnetic powder BN@Fe_(3)O_(4)had been successfully *** the filling amount of BN@Fe_(3)O_(4)reached 27.5 vol%,the out-of-plane thermal conductivity of the composite material was 1.758 W m^(-1)K^(-1),which was 982.12%that of pure *** this point,the mechanical behaviour and insulation performance of EP composite materials can be effectively guaranteed at the same order of magnitude as pure EP performance.
Oil-paper insulation material is an essential component for oil-filled transformers,and polyimide(PI)insulation paper is a novel material in the field of *** improvement of insulation class for insulation paper has ga...
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Oil-paper insulation material is an essential component for oil-filled transformers,and polyimide(PI)insulation paper is a novel material in the field of *** improvement of insulation class for insulation paper has gained significant attention in recent *** this study,SiO_(2)nanoparticles were modified with a silane coupling agent(KH550),and the KH550-SiO_(2)was added to the fibre membrane through in situ *** chemical composition and microcosmic characteristics of the PI porous fibre membrane were characterised using FT-IR and SEM FT-IR and ***-quently,the dielectric constant of the composite paper was reduced to 2.3 upon adding 3 wt%of KH550-SiO_(2),and the dielectric strength reached its maximum value of 85 kV/*** results demonstrate that the insulation performance of the KH550-SiO_(2)/PI composite was significantly improved due to the incorporation of nano-SiO_(2).This establishes an efficient approach for achieving excellent electrical and thermal properties in practical applications using the KH550-SiO_(2)/PI fibre membrane.
In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search spa...
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In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search space with different complexity according to various *** rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture *** this in mind,we propose a faster and more efficient differentiable architecture search method,***,we introduce a more efficient search space enriched by the introduction of two redefined convolution ***,we utilize a more efficient architectural parameter regularization method,mitigating the overfitting problem during the search process and reducing the error brought about by gradient ***,we introduce a natural exponential cosine annealing method to make the learning rate of the neural network training process more suitable for the search ***,group convolution and data augmentation are employed to reduce the computational ***,through extensive experiments on several public datasets,we demonstrate that our method can more swiftly search for better-performing neural network architectures in a more efficient search space,thus validating the effectiveness of our approach.
Zero-shot learning enables the recognition of new class samples by migrating models learned from semanticfeatures and existing sample features to things that have never been seen before. The problems of consistencyof ...
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Zero-shot learning enables the recognition of new class samples by migrating models learned from semanticfeatures and existing sample features to things that have never been seen before. The problems of consistencyof different types of features and domain shift problems are two of the critical issues in zero-shot learning. Toaddress both of these issues, this paper proposes a new modeling structure. The traditional approach mappedsemantic features and visual features into the same feature space;based on this, a dual discriminator approachis used in the proposed model. This dual discriminator approach can further enhance the consistency betweensemantic and visual features. At the same time, this approach can also align unseen class semantic features andtraining set samples, providing a portion of information about the unseen classes. In addition, a new feature fusionmethod is proposed in the model. This method is equivalent to adding perturbation to the seen class features,which can reduce the degree to which the classification results in the model are biased towards the seen *** the same time, this feature fusion method can provide part of the information of the unseen classes, improvingits classification accuracy in generalized zero-shot learning and reducing domain bias. The proposed method isvalidated and compared with othermethods on four datasets, and fromthe experimental results, it can be seen thatthe method proposed in this paper achieves promising results.
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