LMF-Net: A Learnable Multimodal Fusion Network for Semantic Segmentation of Remote Sensing Data by Jihao Li, Wenkai Zhang, Weihang Zhang, Ruixue Zhou, Chongyang Li, Boyuan Tong, Xian Sun, Kun Fu

“…The further mining for cross-modal features is comparatively insufficient in heterogeneous data fusion. In addition, complex structures also lead to relatively heavy computation burden. …”
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Identification of Parkinson’s disease using MRI and genetic data from the PPMI cohort: an improved machine learning fusion approach by Yifeng Yang, Liangyun Hu, Yang Chen, Weidong Gu, Guangwu Lin, YuanZhong Xie, Shengdong Nie

“…ObjectiveThis study aim to leverage advanced machine learning techniques to develop and validate novel MRI imaging features and single nucleotide polymorphism (SNP) gene data fusion methodologies to enhance the early identification and diagnosis of Parkinson’s disease (PD).MethodsWe leveraged a comprehensive dataset from the Parkinson’s Progression Markers Initiative (PPMI), which includes high-resolution neuroimaging data, genetic single-nucleotide polymorphism (SNP) profiles, and detailed clinical information from individuals with early-stage PD and healthy controls. …”
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Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupl... by Haiyan Fu, Ou Hu, Lu Xu, Yao Fan, Qiong Shi, Xiaoming Guo, Wei Lan, Tianming Yang, Shunping Xie, Yuanbin She

“…However, compared with individual instrumental data, data fusion was more adequate for modeling the antioxidant activities of samples with RMSEP of 0.0065. …”
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A CNN-RF Hybrid Approach for Rice Paddy Fields Mapping in Indramayu Using Sentinel-1 and Sentinel-2 Data by Dodi Sudiana, Mia Rizkinia, Rahmat Arief, Tiara De Arifani, Anugrah Indah Lestari, Dony Kushardono, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo

“…This research focuses on developing a classification model for rice paddy field mapping using remote sensing with radar and optical data fusion, including input variations in polarization, texture, and optical derivative indices. …”
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A land-cover-assisted super-resolution model for retrospective reconstruction of MODIS-like NDVI data across the continental United States by blending Landcover300m and GIMMS NDVI3... by Zhicheng Zhang, Zhenhua Xiong, Xuewen Zhou, Kun Xiao, Wei Wu, Qinchuan Xin

“…The absence of such data prior to the launch of MODIS in 2000 necessitates the retrospective reconstruction of MODIS-like datasets. While data fusion techniques are capable of generating spatiotemporally continuous data, challenges remain in capturing interannual variation of land surface dynamics at a spatial resolution where real observation data are lacking. …”
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The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets by Theresa Willem, Alessandro Wollek, Theodor Cheslerean-Boghiu, Martha Kenney, Alena Buyx

“…We first present an exploratory, quantitative study that assesses the effects when including or excluding each of the unique categorical data features of the PAD-UFES 20 dataset for training a transformer-based model using a data fusion algorithm. We then pair our quantitative analysis with a qualitative examination of the data categories based on interviews with the dataset authors. …”
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Advancements and trends in mangrove species mapping based on remote sensing: A comprehensive review and knowledge visualization by Yuqi Wu, Chunyan Lu, Kexin Wu, Wenna Gao, Nuocheng Yang, Jingwen Lin

“…Research in this field still faces several challenges in data fusion, classification algorithm enhancement, increased number of classification species, and large-scale long-term mapping. …”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…In this paper, the state of the art in yield prediction has been advanced due to the employment of multi-source data fusion, sophisticated feature engineering, and advanced neural network architectures. …”
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Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging by Yixuan Zheng, Hongyuan Ning, Eason Rangarajan, Aban Merali, Adam Geale, Lukas Lindenroth, Zhouyang Xu, Weizhao Wang, Philipp Kruse, Steven Morris, Liang Ye, Xinyi Fu, Kawal Rhode, Richard James Housden

“…The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. …”
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UAV Hyperspectral Remote Sensing Image Classification: A Systematic Review by Zhen Zhang, Lehao Huang, Qingwang Wang, Linhuan Jiang, Yemao Qi, Shunyuan Wang, Tao Shen, Bo-Hui Tang, Yanfeng Gu

“…Furthermore, this article delves into cutting-edge research trends, such as lightweight model development, hyperspectral large models, multisource data fusion, and model interpretability, while also highlighting future trends for UAV hyperspectral remote sensing classification technology, particularly in real-time monitoring and intelligent applications.…”
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Artificial Intelligence–Related Dental Research: Bibliometric and Altmetric Analysis by Wei Lu, Xueqian Yu, Yueyang Li, Yi Cao, Yanning Chen, Fang Hua

“…Attention mechanism, explainable AI, multimodal data fusion, and AI-generated text assistants necessitate future research and exploration.…”
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