Intelligent Selection Recommendation Algorithm in the "Double" Mechanism

Tang, Chunhua; Tang, Jin-jun; Chi, En-xian

doi:10.12783/dtcse/wcne2017/19880

Cited by 2 publications

(3 citation statements)

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“…The Head is divided into three or four detection heads depending on the configuration file, responsible for final classification and regression on different-sized feature maps. It outputs classification information, background/foreground judgments, and coordinate information [16][17][18].…”

Section: Object Detection Methods Based On Yolov7mentioning

confidence: 99%

Improving the Application of Yolov7 Algorithm in Pin-Losing-Bolts Detection on Power Transmission Lines

Zhao,

Zhen

2024

FSE

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A method for bolt deficiency detection on power transmission lines based on YOLOv7 is proposed to address the issues of low detection accuracy and high false negatives in current unmanned aerial vehicle (UAV) inspections. In the Neck module, the existing feature fusion structure is modified by directly combining deep and shallow feature information across adjacent scale feature maps. The prior box sizes in the original YOLOv7 are adjusted to better fit the dimensions and aspect ratios of bolt targets. The improved YOLOv7 algorithm enhances the learning capability of bolt feature information. Experimental results on the bolt deficiency dataset using this method show a 6% increase in precision and a 0.6% increase in mAP_0.5. The experiments demonstrate that the improved method enhances the detection ability of bolt deficiencies on power transmission lines and has practical value in intelligent inspections.

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Section: Object Detection Methods Based On Yolov7mentioning

confidence: 99%

Improving the Application of Yolov7 Algorithm in Pin-Losing-Bolts Detection on Power Transmission Lines

Zhao,

Zhen

2024

FSE

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“…The self-attentive mechanism differs from the general attention mechanism in that the Query, Key and Value come from the same data source, and the purpose is to obtain the connection between the data of the data sources. The self-attention mechanism can be formalized as Equation (2).…”

Section: 𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝑄 𝐾 𝑉mentioning

confidence: 99%

“…Knowledge Graph (KG) contains a large amount of auxiliary information and can provide an effective way to organize and manage a large amount of information. Introducing Knowledge Graph in recommendation algorithms can help to explore deeper potential connections between users and items and enhance the recommendation results [2].…”

Section: Introductionmentioning

confidence: 99%

Research on Personalized Recommendation Algorithm of Internet Platform Goods Based on Knowledge Graph

Nie

2023

HSET

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Personalized recommendation method is an effective means to filter out the information users need from a large amount of information, which is rich in practical value. Personalized recommendation methods are maturing, and many e-commerce platforms have been using different forms of recommendation methods with great success. In the recommendation systems of large-scale e-commerce platforms, traditional recommendation algorithms represented by collaborative filtering are modeled only based on users' rating data, and sparse user-project interaction data and cold start are two inevitable problems. The introduction of knowledge graphs in recommendation systems can effectively solve these problems because of their rich knowledge content and powerful relationship processing capability. In this paper, we study the personalized recommendation algorithm based on knowledge graph as auxiliary information, and use the temporal information of user-item interaction in the graph to model users' interests over time at a finer granularity, taking into account the problem of high training time cost of the model due to frequent updates of the knowledge graph when recommending to users dynamically. The article proposes the Interactive Knowledge-Aware Attention Network Algorithmic Model for Recommendations (IKANAM) and conducts comparison experiments on public datasets. The results show that the IKANAM recommendation algorithm can effectively improve the effectiveness of personalized recommendation of products on Internet platforms.

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Intelligent Selection Recommendation Algorithm in the "Double" Mechanism

Cited by 2 publications

References 0 publications

Improving the Application of Yolov7 Algorithm in Pin-Losing-Bolts Detection on Power Transmission Lines

Improving the Application of Yolov7 Algorithm in Pin-Losing-Bolts Detection on Power Transmission Lines

Research on Personalized Recommendation Algorithm of Internet Platform Goods Based on Knowledge Graph

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