Titlebook: Communications, Signal Processing, and Systems; Proceedings of the 1 Qilian Liang,Wei Wang,Baoju Zhang Conference proceedings 2023 The Edit

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書(shū)目名稱Communications, Signal Processing, and Systems影響因子(影響力)




書(shū)目名稱Communications, Signal Processing, and Systems影響因子(影響力)學(xué)科排名




書(shū)目名稱Communications, Signal Processing, and Systems網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Communications, Signal Processing, and Systems網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Communications, Signal Processing, and Systems被引頻次




書(shū)目名稱Communications, Signal Processing, and Systems被引頻次學(xué)科排名




書(shū)目名稱Communications, Signal Processing, and Systems年度引用




書(shū)目名稱Communications, Signal Processing, and Systems年度引用學(xué)科排名




書(shū)目名稱Communications, Signal Processing, and Systems讀者反饋




書(shū)目名稱Communications, Signal Processing, and Systems讀者反饋學(xué)科排名

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,Cross-Modal Two-Stream Target Focused Network for?Video Anomaly Detection, video. Training an unsupervised learning model on normal data is one of the most prevalent VAD paradigms owning to rare abnormal snippets. However, anomaly related and irrelated information sharing feature space will degrade the representation ability of the model for abnormal events. In this artic

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,Fall Detection in?the?Wild: An Intelligent Emergency Assistance System,s of serious injuries caused by falls. In this paper, we propose an IEAS, a framework that integrates deep learning-based fall detection and edge computing-based local processing. First, we introduce a novel challenging benchmark dataset, called WildFall, to better evaluate fall detection models in