This research delves into the prompt identification and prediction of Polycystic Ovary Syndrome utilizing machine learning, specifically focusing on the XGBoost algorithm. Through an examination of data gathered from ...
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The innovation for entrepreneurial systems and the advocacy to enact policies that institutionalise it had recently flooded the literature. Every system has fundamental principles responsible for their state, progress...
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The provision of feedback that is both effective and constructive is of critical importance in the process of enhancing the shopping mall experience for customers. It is a very useful instrument for identifying areas ...
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This paper proposes a new population-based global optimization algorithm, Ọdịgbo Metaheuristic Optimization Algorithm–ỌMOA, for solving complex bounded-constraint/single objective real-parameter problems found in mos...
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This study addresses the critical issue of child abuse in digital communications by developing advanced machine learning and deep learning models for detecting child abusive texts in the Bengali language on online pla...
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In this survey paper, the critical security and privacy issues in cloud computing are taken into consideration, and made use of improving data security measures and confidences concerning sensitive information against...
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Great progress has been made toward accurate face detection in recent ***,the heavy model and expensive computation costs make it difficult to deploy many detectors on mobile and embedded devices where model size and ...
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Great progress has been made toward accurate face detection in recent ***,the heavy model and expensive computation costs make it difficult to deploy many detectors on mobile and embedded devices where model size and latency are highly *** this paper,we present a millisecond-level anchor-free face detector,YuNet,which is specifically designed for edge *** are several key contributions in improving the efficiency-accuracy ***,we analyse the influential state-of-theart face detectors in recent years and summarize the rules to reduce the size of ***,a lightweight face detector,YuNet,is *** detector contains a tiny and efficient feature extraction backbone and a simplified pyramid feature fusion *** the best of our knowledge,YuNet has the best trade-off between accuracy and *** has only 75856 parameters and is less than 1/5 of other small-size *** addition,a training strategy is presented for the tiny face detector,and it can effectively train models with the same distribution of the training *** proposed YuNet achieves 81.1%mAP(single-scale)on the WIDER FACE validation hard track with a high inference efficiency(Intel i7-12700K:1.6ms per frame at 320×320).Because of its unique advantages,the repository for YuNet and its predecessors has been popular at GitHub and gained more than 11K stars at https://***/ShiqiYu/***:Face detection,object detection,computer version,lightweight,inference efficiency,anchor-free mechanism.
The digital era has brought a surge in the amount of data generated, increasing the need for data security across individuals, organizations, and governments. Protecting sensitive information from unauthorized access ...
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Solar cell defect detection is crucial for quality inspection in photovoltaic power generation *** the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challengin...
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Solar cell defect detection is crucial for quality inspection in photovoltaic power generation *** the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective ***,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective *** paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these *** network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation ***,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information *** order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target ***,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter ***,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and *** and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon *** results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.
In recent years, healthcare in smart cities is considered as significant to create a more resilient and well-informed healthcare ecosystem. The integration of cloud computing in healthcare industry has facilitated the...
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