With the development of smart electricity technology and demand response, optimization of household electricity consumption behavior has become an important research element for energy saving in residential buildings....
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In order to improve the identification efficiency of garbage cleaning, we improve the identification speed and accuracy by studying the data and models of garbage classification and detection, so as to achieve higher ...
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Temperature change is a complex atmospheric phenomenon. Even the ERA5-Land atmospheric reanalysis temperature dataset with the highest accuracy currently has errors with the actual observed temperature. This study cap...
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As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy conce...
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As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh Lynn Shacham(BLS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
Deep learning methods, known for their powerful feature learning and classification capabilities, are widely used in phishing detection. To improve accuracy, this study proposes DPMLF (Deep Learning Phishing Detection...
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Session-based recommendation aims to generate personalized recommendations based on user behaviors within a browsing session. The traditional graph neural network (GNN) methods focus on modeling pair-wise relationship...
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This paper discusses how to organically combine image retrieval with data mining, image reconstruction and other related technologies. It makes use of the prior knowledge and rich images contained in the bigdata, and...
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Due to the ability to automatically extract phishing features without relying on expert knowledge, deep learning methods have been widely applied in the research of phishing email classification and detection. However...
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In recent years,the number of patientswith colon disease has increased *** polyps are the precursor lesions of colon *** not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patie...
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In recent years,the number of patientswith colon disease has increased *** polyps are the precursor lesions of colon *** not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon ***,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis *** order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant *** help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of *** results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp *** to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.
The unprecedented growth of industrial Internet of Things applications requires the evolution of wireless networked control system (WNCS). However, independent designs between communication and control without conside...
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