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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Zhanjun Si,Yijie Pan Conference proceeding

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A Survey: Feature Fusion Method for Object Detection Fieldopological fusion structures. The paper conducts analyses and summarizes the mechanisms of these two types of structures, introduced the evaluation dataset and evaluation indicators, accompanied by a collation of open-source codes for mainstream feature fusion architectures. Ultimately, through syst
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EfficientPose: A Lightweight and Efficient Model with Transformer for Human Pose Estimationntroduced into the model. Meanwhile, to overcome the issue of excessively long training time for lightweight models, a novel iterative training strategy is proposed to fully unleash the potential of EfficientPose. To validate the effectiveness of EfficientPose model, extensive comparative experiment
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Graph Convolution Recommendation Algorithm Integrating Multi-relationship Preferencespagation layer to achieve prediction. Experimental verification was conducted on the Lastfm data set. The experimental results show that the performance of this method is the best, proving the effectiveness of the method.
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Joint Prior Relation Enhancement and Non-autoregressive Decoding for Document-Level Event Extractionon-autoregressive decoding algorithm based on an optimized pseudo triggers selection strategy, which efficiently extracts multiple event argument combinations in a joint parallel manner, significantly improving the efficiency of model extraction. Comparative experiments validate the outstanding perf
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0302-9743 applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology..978-981-97-5587-5978-981-97-5588-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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P. Jürgens,C. Panteliades,G. Fondalinskicomplexity as network size expands, and imbalanced datasets typically lead to reduced model accuracy and generalization. Lastly, it presents several promising avenues for future research in the field.
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