Multimodal heterogeneous graph fusion for automated obstructive sleep apnea-hypopnea syndrome diagnosis by Haoyu Wang, Xihe Qiu, Bin Li, Xiaoyu Tan, Jingjing Huang

“…This study presents a novel heterogeneous graph convolutional fusion network (HeteroGCFNet) leveraging multimodal physiological signals and domain knowledge for automated OSAHS diagnosis. …”
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Classification of Emerging Scoliosis in Congenital Scoliosis After Hemivertebra Resection and Short Segmental Fusion by Chenkai Li, Xiaohan Ye, Bingtai Han, You Du, Yiwei Zhao, Dihan Sun, Shengru Wang, Jianguo Zhang

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Microstructural and mechanical properties of ultrasonically assisted titanium-steel dissimilar metal fusion welds by Xiaohu Hao, Xinlong Wei, Shuhua Li, Zeqin Cui, Dejun Yan, Weiguo Li

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A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…The enhanced features were then processed through the multiscale feature fusion module to obtain multiscale image feature information at different depths to obtain more robust fused features. …”
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Frequency and Texture Aware Multi-Domain Feature Fusion for Remote Sensing Scene Classification by Russo Ashraf, Kang-Hyun Jo

“…Delving into these complexities, the Efficient Spectral Inception Former (ESIF) architecture is proposed, which introduces a novel paradigm to RS scene classification by integrating multi-domain feature fusion of the spatial, texture, and spectral (frequency) domains. …”
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FcFNet: A Challenge-Based Feature Complementary Fusion Network for RGBT Tracking by Wensheng Wang, Congjian Li, Di Zhang, Huihui Zhou, Mingli Xie, Haoran Zhou, Kun Fu

“…In this work, we propose a novel RGBT tracking model, called challenge-based Feature complementary Fusion Network (FcFNet), especially aiming at noncooperative scenarios. …”
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Design of home fire detection system based on wireless multi-sensor data fusion by Wenbin CHENG, Lei DU, Yiyi LIU

Subjects: “…multi-sensor data fusion…”
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Image experience prediction for historic districts using a CNN-transformer fusion model by Youping Teng, Weijia Wang

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Leading-logarithmic threshold resummation of Higgs production in gluon fusion at next-to-leading power by Martin Beneke, Mathias Garny, Sebastian Jaskiewicz, Robert Szafron, Leonardo Vernazza, Jian Wang

“…. , near the kinematic threshold z = m H 2 / s ̂ → 1 $$ z={m}_H^2/\hat{s}\to 1 $$ at next-to-leading power in the expansion in (1 − z) for Higgs production in gluon fusion. We highlight the new contributions compared to Drell-Yan production in quark-antiquark annihilation and show that the final result can be obtained to all orders by the substitution of the colour factor CF → CA, confirming previous fixed-order results. …”
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Lie Detection Technology of Bimodal Feature Fusion Based on Domain Adversarial Neural Networks by Yan Zhou, Feng Bu

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Block-chain abnormal transaction detection method based on adaptive multi-feature fusion by Huijuan ZHU, Jinfu CHEN, Zhiyuan LI, Shangnan YIN

“…Aiming at the problem that the performance of intelligent detection models was limited by the representation ability of original data (features), a residual network structure ResNet-32 was designed to automatically mine the intricate association relationship between original features, so as to actively learn the high-level abstract features with rich semantic information.Low-level features were more transaction content descriptive, although their distinguishing ability was weaker than that of the high-level features.How to integrate them together to obtain complementary advantages was the key to improve the detection performance.Therefore, multi feature fusion methods were proposed to bridge the gap between the two kinds of features.Moreover, these fusion methods can automatically remove the noise and redundant information from the integrated features and further absorb the cross information, to acquire the most distinctive features.Finally, block-chain abnormal transaction detection model (BATDet) was proposed based on the above presented methods, and its effectiveness in the abnormal transaction detection is verified.…”
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IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition by George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos

“…IncSAR combines the power of a Vision Transformer (ViT) and a custom-designed Convolutional Neural Network (CNN) in a dual-branch architecture, integrated via a late-fusion strategy. Additionally, we explore the use of TinyViT to reduce computational complexity and propose an attention mechanism to dynamically enhance feature representation. …”
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Two-Stage Degradation Assessment and Prediction Method for Aircraft Engine Based on Data Fusion by Hongsheng Yan, Hongfu Zuo, Jianzhong Sun, Di Zhou, Han Wang

“…In order to realize the performance degradation assessment and remaining useful life (RUL) prediction of aeroengine, this paper proposes a two-stage assessment and prediction method based on data fusion. First, the standard deviation merged by multiple selected features is used as the health indicator to characterize the engine performance. …”
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The telecommunications customer service model based on big data and data fusion strategy research by Yongmei Gao, Chunhua Ju, Fuguang Bao

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Keratoconus disease classification with multimodel fusion and vision transformer: a pretrained model approach by Shokufeh Yaraghi, Toktam Khatibi

“…These models have been trained on large datasets and have demonstrated strong performance in various computer vision tasks.The extracted features from the three pretrained models were fused using a feature fusion technique. This fusion aimed to combine the strengths of each model and capture a more comprehensive representation of the input images. …”
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CONDITION ASSESSMENT OF THIN-WALLED ROBOT BEARING BASED ON MULITI-SENSOR DATA FUSION by LIU Yang, XIE TanCheng, XU YanWei, WANG Bing, LI BanHu

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HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion by Yufei Zhao, Hua Liu, Hua Duan

“…To address these issues, this paper proposes HGNN-GAMS: a Heterogeneous Graph Neural Network for Graph Attribute Mining and Semantic Fusion. The model comprises two main components: graph attribute fusion and semantic aggregation. …”
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Predicting conversion of Alzheimer’s disease based on multi-modal fusion of neuroimaging and genetic data by Yang Xi, Qian Wang, Chenxue Wu, Lu Zhang, Ying Chen, Zhu Lan

“…We proposed a classification method of sMCIs and pMCIs based on multi-modality data fusion of single-nucleotide polymorphisms (SNP), ratio of gray matter volume (RGV) obtained by morphometric measures, and sMRI images to predict the progression of AD. …”
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GEO GOIDACI. THE FUSION OF THE ARTS: SCULPTURE AND MUSIC; GRAPHIC, PHOTO AND DIGITAL ART - INTERVIEW - by Gabriela Coca

“…In this interview, we try to come close to the artist Geo Goidaci, taking in his entire personality, address­ing his creative style, his conception about art and the fusion of the arts in his activity and his life. …”
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Simulation of Static Loading on the Automatic Folding Clothes Hanger by Using Autodesk Fusion 360 by Sukendro Broto Sasongko, Agung Subekti

“…<p>Simulation of the static loading to the folding frame of the clothes hanger investigated by using Software Autodesk Fusion 360. The strength of the folding frame is important during hanging the clothes weight. …”
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