Fusion of Multi-Task Neurophysiological Data to Enhance the Detection of Attention- Deficit/Hyperactivity Disorder by Kai-Feng Zhang, Shih-Ching Yeh, Eric Hsiao-Kuang Wu, Xiu Xu, Ho-Jung Tsai, Chun-Chuan Chen

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Research on load frequency control system attack detection method based on multi-model fusion by Feng Zheng, Weixun Li, Huifeng Li, Libo Yang, Zengjie Sun

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Regional Ecological Environment Quality Prediction Based on Multi-Model Fusion by Yiquan Song, Zhengwei Li, Baoquan Wei

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OncoFusion: Multi-Model Approach for Generalized and Ovarian Cancer Detection with Stacked Ensembles by Zaware Sarika, Neharkar Rutuja, Sayyad Ayesha, Patil Aarya, Mulla Salma

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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

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Research and implementation of text classification method for customer service orders based on multi-model fusion by Liang ZHANG, Xiaoju DAI, Rong ZHENG, Tongze He

“…Due to the large amount of order categories and their hierarchical associations, traditional manual order classification method of customer service in telecom call center has the problems of long archiving time, low efficiency and unsustainable accuracy.To solve this problem, a novel text classification algorithm based on multi-model fusion was proposed, which intelligently classify orders with multiple models based on data characteristics and their hierarchical associations, the effectiveness of this method was verified.The current manual operation process was optimized and operation efficiency was enhanced, which support the intelligent transformation and upgradation of existing customer service system.…”
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A Comprehensive Review of Multiple Physical and Data-Driven Model Fusion Methods for Accurate Lithium-Ion Battery Inner State Factor Estimation by Junjie Tao, Shunli Wang, Wen Cao, Carlos Fernandez, Frede Blaabjerg

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Prediction of Student Academic Performance Utilizing a Multi-Model Fusion Approach in the Realm of Machine Learning by Wei Zou, Wei Zhong, Junzhen Du, Lingyun Yuan

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Multi-Model Synergistic Satellite-Derived Bathymetry Fusion Approach Based on Mamba Coral Reef Habitat Classification by Xuechun Zhang, Yi Ma, Feifei Zhang, Zhongwei Li, Jingyu Zhang

“…In this study, refined classification was performed for complex seafloor sediment and geomorphic features in coral reef habitats. A multi-model synergistic SDB fusion approach constrained by coral reef habitat classification based on the deep learning framework Mamba was constructed. …”
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A multi-model feature fusion based transfer learning with heuristic search for copy-move video forgery detection by Hessa Alfraihi, Muhammad Swaileh A. Alzaidi, Hamed Alqahtani, Abdulbasit A. Darem, Ali M. Al-Sharafi, Ahmad A. Alzahrani, Menwa Alshammeri, Abdulwhab Alkharashi

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A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

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Synergistic Multi-Model Approach for GPR Data Interpretation: Forward Modeling and Robust Object Detection by Hang Zhang, Zhijie Ma, Xinyu Fan, Feifei Hou

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Flight delay stacking ensemble prediction model for severe weather by SUN Yue, DING Jianli

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Flight delay stacking ensemble prediction model for severe weather by SUN Yue, DING Jianli

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A Joint Extraction Method of Entity Relations in Aquaculture Long Text Using N-Gram Fusion by BI Tiantian, ZHANG Sijia, SUN Xufei, WANG Shuitao, WANG Yihan, AN Zongshi

“…To solve the problem of misjudgment and loss of valid information caused by a large amount of irrelevant information in aquaculture long text, a joint extraction method of entity relations based on N-Gram fusion was proposed. Firstly, the multi-model fusion algorithm is used to extract the text matrix feature map based on BERT initialization, and then the cascading BiLSTM is used to extract the deep features. …”
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Cross-Modal Data Fusion via Vision-Language Model for Crop Disease Recognition by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

“…To address this problem, we proposed a cross-modal data fusion via a vision-language model for crop disease recognition. …”
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Roadside Perception System Based on LiDAR and Millimeter-wave Radar Fusion in Mining Area by JIANG Liangyu

“…In view of the multi-sensor fusion technology of LiDAR and millimeter-wave radar and its advantages, a tracking algorithm based on Kalman filter and interactive multi-model (IMM) is proposed. …”
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Smart Grain Storage Solution: Integrated Deep Learning Framework for Grain Storage Monitoring and Risk Alert by Xinze Li, Wenfu Wu, Hongpeng Guo, Yunshandan Wu, Shuyao Li, Wenyue Wang, Yanhui Lu

“…In order to overcome the notable limitations of current methods for monitoring grain storage states, particularly in the early warning of potential risks and the analysis of the spatial distribution of grain temperatures within the granary, this study proposes a multi-model fusion approach based on a deep learning framework for grain storage state monitoring and risk alert. …”
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Stacking Ensemble Learning and SHAP-Based Insights for Urban Air Quality Forecasting: Evidence from Shenyang and Global Implications by Zhaoxin Xu, Huajian Zhang, Andong Zhai, Chunyu Kong, Jinping Zhang

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Frobenius deep feature fusion architecture to detect diabetic retinopathy by C. Priyadharsini, Y. Asnath Victy Phamila

“…The proposed approach delves into various phases- data collection and data pre-processing, feature extraction from VGG16 and Densenet201, feature selection using Random Forest, feature fusion using Frobenius norm, and classification using stacked ensembling of XGBoost classifier and ExtraTreeClassifier with SVC as meta-learner. …”
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