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MSC-YOLO:Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

Computers, Materials & Continua 2024年第4期79卷 983-1003页

作者： Xiangyan Tang chengchun ruan Xiulai Li Binbin Li Cebin Fu School of Computer Science and Technology Hainan UniversityHaikou570228China Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China School of Cyberspace Security(School of Cryptology) Hainan UniversityHaikou570228China

Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion *** enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial *** build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small *** replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small ***,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple *** module enhances the perception of spatial contextual features and the utilizationof multiscale feature *** the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.

关键词： Small object detection YOLOv7 multi-scale attention spatial context

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An Adaptive DDoS Detection and Classification Method in Blockchain Using an Integrated Multi-Models

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Computers, Materials & Continua 2023年第12期77卷 3265-3288页

作者： Xiulai Li Jieren Cheng chengchun ruan Bin Zhang Xiangyan Tang Mengzhe Sun School of Computer Science and Technology Hainan UniversityHaikou570228China School of Cyberspace Security Hainan UniversityHaikou570228China Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China Hainan Hairui Zhong Chuang Technol Co. Ltd.Haikou570228China School of Information Science and Technology Qiongtai Normal UniversityHaikou570228China

With the rising adoption of blockchain technology due to its decentralized,secure,and transparent features,ensuring its resilience against network threats,especially Distributed Denial of Service(DDoS)attacks,is *** research addresses the vulnerability of blockchain systems to DDoS assaults,which undermine their core decentralized characteristics,posing threats to their security and *** have devised a novel adaptive integration technique for the detection and identification of varied DDoS *** ensure the robustness and validity of our approach,a dataset amalgamating multiple DDoS attacks was derived from the CIC-DDoS2019 *** this,our methodology was applied to detect DDoS threats and further classify them into seven unique attack *** cope with the broad spectrum of DDoS attack variations,a holistic framework has been pro-posed that seamlessly integrates five machine learning models:Gate Recurrent Unit(GRU),Convolutional Neural Networks(CNN),Long-Short Term Memory(LSTM),Deep Neural Networks(DNN),and Support Vector Machine(SVM).The innovative aspect of our framework is the introduction of a dynamic weight adjustment mechanism,enhancing the system’s *** results substantiate the superiority of our ensemble method in comparison to singular models across various evaluation *** framework displayed remarkable accuracy,with rates reaching 99.71%for detection and 87.62%for classification *** developing a comprehensive and adaptive methodology,this study paves the way for strengthening the defense mechanisms of blockchain systems against DDoS *** ensemble approach,combined with the dynamic weight adjustment,offers promise in ensuring blockchain’s enduring security and trustworthiness.

关键词： Blockchain DDoS multi-models adaptive detection

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