Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/n/image/663589.jpg

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Paper Recommendation with Multi-view Knowledge-Aware Attentive Network solve problems such as data sparsity faced by traditional recommendation methods and used GNN-based techniques to mine the features of users and papers. However, existing work has not emphasized the quality of the knowledge graph construction, and has not optimized the modeling method from the scen

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Research on?Automatic Segmentation Algorithm of?Brain Tumor Image Based on?Multi-sequence Self-superllenging due to the limitations and intricacy of manual delineation. This paper presents a brain tumor image segmentation framework that addresses these challenges by leveraging multiple sequence information. The framework consists of encoder, decoder, and data fusion modules. The encoder incorporat

Inscrutable

An Effective Morphological Analysis Framework of Intracranial Artery in 3D Digital Subtraction Angiorvention surgery. However, this task often comes with challenges of large-scale image and memory constraints. In this paper, an effective two-stage framework is proposed for fully automatic morphological analysis of intracranial artery. In the first stage, the proposed Region-Global Fusion Network (

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Incompetent

TCNet: Texture and Contour-Aware Model for Bone Marrow Smear Region of Interest Selection it is essential to select uniformly distributed and clear sections as regions of interest (ROIs). However, current ROI selection models have not considered the characteristics of bone marrow smears, resulting in poor performance in practical applications. By comparing bone marrow smear ROIs and non