Improved identification and tracking of three-dimensional eddies in the Southern Ocean utilizing 3D-U-Res-Net by Chang Liu, Xiayan Lin, Xiayan Lin, Guangjun Xu, Guangjun Xu, Guoqing Han, Yu Liu

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Watershed Health Prediction based on Surface Water Quality Variables (Case Study: Taleghan Watershed) by Payam Ebrahimi, Ali Salajegheh, Mohsen Mohseni Saravi, Arash Malekian, Amir Sadoddin

“…Since in the last decade, due to the use of water resources and its pollution, this vital source has changed, the information of its status in the coming years can play an important role in environmental planning and sustainability of human geography. …”
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Microwave Sensors and Their Applications in Permittivity Measurement by Changjun Liu, Chongwei Liao, Yujie Peng, Weixin Zhang, Bo Wu, Peixiang Yang

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Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

“…Precisely recognizing diseases in tomato leaves plays a crucial role in enhancing the health, productivity, and quality of tomato crops. …”
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An Intelligent Track Segment Association Method Based on Characteristic-Aware Attention LSTM Network by Jiadi Qi, Xiaoke Lu, Jinping Sun

“…Accurate track segment association plays an important role in modern sensor data processing systems to ensure the temporal and spatial consistency of target information. …”
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Littératie algorithmique et pratiques médiatiques des jeunes à Bruxelles by Sylvain Malcorps, Arnaud Claes, Thibault Philippette, Marie Dufrasne

“…Recommendation algorithms play an undeniable role in the access to information, and are aimed at making browsing easier for users by recommending the most "relevant" content according to a series of criteria selected by their designers. …”
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Deep learning for sea surface temperature applications: A comprehensive bibliometric analysis and methodological approach by Redouane Larbi Boufeniza, Luo Jingjia, Kemal Adem Abdela, Karam Alsafadi, Mohammad M Alsahli

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PBD-YOLO: Dual-Strategy Integration of Multi-Scale Feature Fusion and Weak Texture Enhancement for Lightweight Particleboard Surface Defect Detection by Haomeng Guo, Zheming Chai, Huize Dai, Lei Yan, Pengle Cheng, Jianhua Yang

“…In order to improve the ability of the algorithm to extract weak texture features, the SPDDEConv (Space to Depth and Difference Enhance Convolution) module was introduced in this study, which reduced the loss of information in the down-sampling process through space-to-depth transformation and enhanced the edge information of weak texture defects through difference convolution. …”
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Recent Advances in Deep Learning-Based Spatiotemporal Fusion Methods for Remote Sensing Images by Zilong Lian, Yulin Zhan, Wenhao Zhang, Zhangjie Wang, Wenbo Liu, Xuhan Huang

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Autoencoder-Based Hyperspectral Unmixing with Simultaneous Number-of-Endmembers Estimation by Atheer Abdullah Alshahrani, Ouiem Bchir, Mohamed Maher Ben Ismail

“…Hyperspectral unmixing plays a fundamental role in mining meaningful information from hyperspectral data. …”
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A Framework for Human Activity Recognition Based on WiFi CSI Signal Enhancement by Jieming Yang, Yanming Liu, Zhiying Liu, Yun Wu, Tianyang Li, Yuehua Yang

“…Human activity recognition using channel state information (CSI) in commercial WiFi devices plays an important role in many applications. …”
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Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…For LiDAR-acquired forest point cloud data, existing two-dimensional (2D) plane-based algorithms for tree trunk detection often suffer from spatial information loss, resulting in reduced accuracy, particularly for tilted trees. …”
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The role of hypoxia-senescence co-related molecular subtypes and prognostic characteristics in hepatocellular carcinoma by Fuqing Chen, Yifan Cai, Xiangmei Chen, Changzhou Chen, Qinliang Fang, Jianming Liu, Yibin Zhang, Jianyin Zhou

“…SVM algorithm was used to classify HCC patients based on HSCRGs. …”
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Doing What Is Right: Role of Social Media Users in Resilience to Disinformation by Karolína Bieliková, Alena Pospíšil Macková, Martina Novotná

“…Active users, who, with their actions, can curate the information environment of others, can play a crucial role in stopping the dissemination of disinformation. …”
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High spatiotemporal resolution vegetation FAPAR estimation from Sentinel-2 based on the spectral invariant theory by Yunzhu Tao, Naijie Peng, Wenjie Fan, Xihan Mu, Husi Letu, Run Ma, Siqi Yang, Qunchao He, Dechao Zhai, Huangzhong Ren

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Offline Single-Polarization Radar Quantitative Precipitation Estimation Based on a Spatiotemporal Deep Fusion Model by Yonghong Zhang, Shiwei Chen, Wei Tian, Guangyi Ma, Shuai Chen

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Point-to-Interval Prediction Method for Key Soil Property Contents Utilizing Multi-Source Spectral Data by Shuyan Liu, Dongyan Huang, Lili Fu, Shengxian Wu, Yanlei Xu, Yibing Chen, Qinglai Zhao

“…Key soil properties play pivotal roles in shaping crop growth and yield outcomes. …”
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Intelligent Decision Making Technique for Handling Game Tactics in Soccer Sports by Karun Madan, Kavita Taneja, Harmunish Taneja

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Interactive Maintenance of Space Station Devices Using Scene Semantic Segmentation by Haoting Liu, Chuanxin Liao, Xikang Li, Zhen Tian, Mengmeng Wang, Haiguang Li, Xiaofei Lu, Zhenhui Guo, Qing Li

“…The atrous spatial pyramid pooling (ASPP) module is also considered to enable an accurate calculation of encoding multi-scale information. Extensive simulation experiment results indicate that the accuracy, precision, and average intersection over the union of the proposed algorithm can be better than 95.0%, 96.0%, and 89.0%, respectively. …”
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A Novel Method for Noise Reduction and Jump Correction of Maglev Gyroscope Rotor Signals Under Instantaneous Perturbations by Di Liu, Zhen Shi, Chenxi Zou, Ziyi Yang, Jifan Li

“…Furthermore, we utilize the stable sampling trend data of the rotor signal as sample data, employing the ARIMA model to accurately predict the missing abnormal jump trend data, thereby ensuring the completeness and coherence of the rotor signal trend information. Experimental results demonstrate that, compared to the original rotor signal, the reconstructed signal processed by the MAF-ARIMA algorithm exhibits an average reduction of 70.58% in standard deviation and an average decrease of 47.31% in the absolute error of azimuth measurement results. …”
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