Titlebook: Data Science; 10th International C Chengzhong Xu,Haiwei Pan,Zeguang Lu Conference proceedings 2024 The Editor(s) (if applicable) and The Au

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書目名稱Data Science影響因子(影響力)




書目名稱Data Science影響因子(影響力)學(xué)科排名




書目名稱Data Science網(wǎng)絡(luò)公開度




書目名稱Data Science網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Data Science被引頻次




書目名稱Data Science被引頻次學(xué)科排名




書目名稱Data Science年度引用




書目名稱Data Science年度引用學(xué)科排名




書目名稱Data Science讀者反饋




書目名稱Data Science讀者反饋學(xué)科排名

表示向前

A Lightweight Edge Network Intrusion Detection System Based on MobileVitthms, and the large resource overhead required to deploy deep learning algorithms to edge networks, we proposes a lightweight intrusion detection system based on MobileViT, which can detect cyber-attack traffic in edge networks with little resource consumption. The system uses smote to balance the d

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Prologue

Enhancing Relevance and Efficiency in Visual Question Generation Through Redundant Object Filtering provides answers. The quality of question generation is vital for the task, but existing methods do not consider the redundant objects brought by Faster RCNN for object detection, leading to meaningless, repetitive questions. To address this, we propose Question Improvement and Redundancy Eliminati

Prologue

Chinese Named Entity Recognition Algorithm Integrating Vocabulary Informationicient learning of Chinese character vocabulary information during the training process. This article proposes an entity recognition model LEBERT-IDGRU-CRF based on BERT and introducing external dictionaries for training. The model performs lexical matching on the data text through an external dicti

aggrieve

WSDSum: Unsupervised Extractive Summarization Based on Word Weight Fusion and Document Dynamic Compaverall content. Numerous prevalent research methods predominantly prioritize the significance of sentences within a document, potentially overlooking the importance of varying keywords within a sentence. Moreover, many methods confine the summarization to information present only in the current docu

針葉樹

Expertise

Multi-modal Variable-Channel Spatial-Temporal Semantic Action Recognition Networktion. However, existing models often lack the spatial-temporal discriminative ability required for fine-grained recognition tasks. To address this issue, we introduce a flexible attention block called Variable-Channel Spatial-Temporal attention (VCSTA) to enhance the discriminative capacity of spati