Long-Term (2015–2024) Daily PM_2.5 Estimation in China by Using XGBoost Combining Empirical Orthogonal Function Decomposition by Jiacheng Jiang, Jiaxin Dong, Yu Ding, Wenjia Ni, Jie Yang, Siwei Li

“…A two-step PM_2.5 estimation model is established based on a machine learning algorithm and a spatio-temporal decomposition method. …”
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Validation of Global Moderate-Resolution FAPAR Products over Boreal Forests in North America Using Harmonized Landsat and Sentinel-2 Data by Yinghui Zhang, Hongliang Fang, Zhongwen Hu, Yao Wang, Sijia Li, Guofeng Wu

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Modeling and Reconstruction of Mixed Functional and Molecular Patterns by Yue Wang, Jianhua Xuan, Rujirutana Srikanchana, Peter L. Choyke

“…Functional medical imaging promises powerful tools for the visualization and elucidation of important disease-causing biological processes in living tissue. Recent research aims to dissect the distribution or expression of multiple biomarkers associated with disease progression or response, where the signals often represent a composite of more than one distinct source independent of spatial resolution. …”
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Current Progress in and Future Visions of Key Technologies of UAV-Borne Multi-Modal Geophysical Exploration for Mineral Exploration: A Scoping Review by Xin Wu, Guo-Qiang Xue, Yan-Bo Wang, Song Cui

“…It is hoped that this research can promote the development of UAV-borne multi-modal observation technology.…”
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Remote sensing for land cover mapping across Victoria, Australia – a machine learning application by Sabah Sabaghy, Mohammad Abuzar, Doug Crawford, Andy McAllister, Kathryn Sheffield

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Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study by Hajin Kim, Bo Kyung Cha, Kyuseok Kim, Youngjin Lee

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Cross Validation of FY3D MWRI Passive Microwave LST With MODIS LST Under Clear-Sky Conditions by Yuting Gong, Huifang Li, Xiuqing Hu, Huanfeng Shen

“…Based on the quality control, temporal matching, and spatial matching, the spatial and temporal distribution were validated between the two LST products from 2019 to 2023. …”
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PEMETAAN PENGGUNAAN LAHAN SAWAH BERDASARKAN PENDEKATAN EKOLOGI BENTANG LAHANMENGGUNAKAN CITRA PEREKAMAN TUNGGAL by Algi Variski Hasibuan, Projo Danoedoro, Sigit Heru Murti

“…The use of ten optical bands in multispectral classification using the maximum likelihood algorithm and convolutional neural network algorithm resulted in twelve land cover classes. …”
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New Hyperspectral Geometry Ratio Index for Monitoring Rice Blast Disease from Leaf Scale to Canopy Scale by Qiong Zheng, Yihao Chen, Qing Xia, Yunfei Zhang, Dan Li, Hao Jiang, Chongyang Wang, Longlong Zhao, Wenjiang Huang, Yingying Dong, Chuntao Wang

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A Rice-Mapping Method with Integrated Automatic Generation of Training Samples and Random Forest Classification Using Google Earth Engine by Yuqing Fan, Debao Yuan, Liuya Zhang, Maochen Zhao, Renxu Yang

“…Due to cloud occlusion and banding problems, data extraction from Landsat series remote sensing images with medium spatial resolution is not optimal. Therefore, this study proposes a rice mapping method (LR) using Google Earth Engine (GEE), which uses Landsat images and integrates automatic generation of training samples and a machine learning algorithm, with the assistance of phenological methods. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…However, the classification of shrublands proved challenging due to their mixed composition and unique spatial patterns, resulting in lower accuracies. Feature importance analysis demonstrated the value of the enhanced map composition, and applying the LandTrendr algorithm simplified the diachronic land use and land cover (LULC) classification and change analysis by supporting automatic training data collection. …”
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Application of Object Based Image Classification Using Orthophotos: A Case Study of the Van-Erciş Earthquake by Aslı Sabuncu, Filiz Sunar

“…The recent advances in digital photogrammetry/remote sensing technology and satellite sensor/camera systems have inspired to emerge new and different research areas and applications. With the development of digital camera technology since 1950's, it has become possible to produce orthophotos with high spatial resolution and positional accuracy. …”
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Progressive multi-scale multi-attention fusion for hyperspectral image classification by Hu Wang, Sixiang Quan, Jun Liu, Hai Xiao, Yingying Peng, Zhihui Wang, Huali Li

“…The effective extraction of features using deep neural networks, followed by the design of efficient and high-precision network algorithm structures, has gradually become a research hotspot. …”
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Long Short-Term Memory-Based Impact of Traffic Incidents: Case Study of Seoul Expressway, Korea by Sang-Hoon Bae, Duy Quang Tran, Bog-gi Park, Huy Tran Quang, Luan Nguyen Huu

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Damage Detection in Plates with the Use of Laser-Measured Mode Shapes by Ziemowit Dworakowski, Kajetan Dziedziech, Pawel Zdziebko, Krzysztof Mendrok

“…This paper presents the use of laser vibrometer measurements to detect and locate damage in a metal plate. An algorithm based on local spatial filters was selected, and for the purpose of comparison, the fault location was also determined based on the wavelet analysis of mode shapes. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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Monitoring of ecological security patterns based on long-term land use changes in Langsa Bay, Indonesia by Jiaojie Zhang, Fengqin Yan, Vincent Lyne, Xuege Wang, Fenzhen Su, Qian Cao, Bin He

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GOES‐R PM2.5 Evaluation and Bias Correction: A Deep Learning Approach by Alqamah Sayeed, Pawan Gupta, Barron Henderson, Shobha Kondragunta, Hai Zhang, Yang Liu

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Fault aware task scheduling in cloud using min-min and DBSCAN by S.M.F D Syed Mustapha, Punit Gupta

“…Clustering the resources clustering and mapping them according to task can also be an option to deal with such task failure or mismanaged resource allocation. Density-based spatial clustering of applications with noise (DBSCAN) is a stochastic approach-based algorithm which has the capability to cluster the resources in a cloud environment. …”
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Feasibility of automating the determination of changes in forest areas using satellite images (Case Study: Central Alborz protected area) by Amir Satari Rad, Behzad Rayegani, Ali Jahani, Hamid Goshtasb Meigooni

“…In this research, the MOD13Q1 product of the MODIS sensor and the normalized vegetation difference index (NDVI) with a spatial resolution of 250 meters and a temporal resolution of 16 days, as well as The MCD12C1 product images of the MODIS sensor with a spatial resolution of 5600 m and a temporal resolution of one year were used in three layers with the classification schemes of the International Geosphere-Biosphere Program (IGBP), University of Maryland (UMD) and the Modis Derived Scheme (LAI). …”
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