Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature ext...
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Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature extraction strategy in this paper,which name is *** this strategy,we design:1)a sandwich attention feature fusion module(SAFF module).Its purpose is to enhance the semantic information of shallow features and resolution of deep features,which is beneficial to small object detection after feature fusion.2)to add a new stage called D-block to alleviate the disadvantages of decreasing spatial resolution when the pooling layer increases the receptive *** method proposed in the new stage replaces the original method of obtaining the P6 feature map and uses the result as the input of the regional proposal network(RPN).In the experimental phase,we use the new strategy to extract *** experiment takes the public dataset of Microsoft Common Objects in Context(MS COCO)object detection and the dataset of Corona Virus Disease 2019(COVID-19)image classification as the experimental object *** results show that the average recognition accuracy of COVID-19 in the classification dataset is improved to 98.163%,and small object detection in object detection tasks is improved by 4.0%.
Image inpainting, aiming at exactly recovering missing pixels from partially observed entries, is typically an ill-posed problem. As a powerful constraint, low-rank priors have been widely applied in image inpainting ...
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Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskde...
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Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.
User authentication on smart devices is crucial to protecting user privacy and device *** to the development of emerging attacks,existing physiological feature-based authentication methods,such as fingerprint,iris,and...
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User authentication on smart devices is crucial to protecting user privacy and device *** to the development of emerging attacks,existing physiological feature-based authentication methods,such as fingerprint,iris,and face recognition are vulnerable to forgery and *** this paper,GestureID,a system that utilizes acoustic sensing technology to distinguish hand features among users,is *** involves using a speaker to send acoustic signals and a microphone to receive the echoes affected by the reflection of the hand movements of the *** ensure system accuracy and effectively distinguish users’gestures,a second-order differential-based phase extraction method is *** method calculates the gradient of received signals to separate the effects of the user’s hand movements on the transmitted signal from the background ***,the secondorder differential phase and phase-dependent acceleration information are used as inputs to a Convolutional Neural Networks-Bidirectional Long Short-Term Memory(CNN-BiLSTM)model to model hand motion *** decrease the time it takes to collect data for new user registration,a transfer learning method is *** involves creating a user authentication model by utilizing a pre-trained gesture recognition *** a result,accurate user authentication can be achieved without requiring extensive amounts of training *** demonstrate that GestureID can achieve 97.8%gesture recognition accuracy and 96.3%user authentication accuracy.
Random sample partition (RSP) is a newly developed data management and processing model for bigdata processing and analysis. To apply the RSP model for bigdata computation tasks, it is very important to measure the ...
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The surging popularity of online movie databases has created a challenge for viewers: choosing a film from a massive library can be overwhelming. In this paper, it proposes to design a new hybrid movie recommendation ...
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The goal of this project is to draw a deeper understanding of the subjective nature behind online product reviews, largely by examining a large dataset received from Amazon that contains numerous star ratings and comm...
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With the continuous improvement of people's living standards, people's income from work has gradually increased, and their remaining savings have also gradually increased. In order to avoid the problem of curr...
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Task scheduling has a significant impact on the resource availability and operation cost of the system in cloud computing. In order to improve the efficiency of task execution in the cloud for a given computational re...
The basis of this project is to investigate whether the YOLO, an object detection algorithm where 'You Only Look Once' constitutes the name, could be applied to develop FMCG management;together with the manage...
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