Leveraging Explainable Artificial Intelligence in Solar Photovoltaic Mappings: Model Explanations and Feature Selection by Eduardo Gomes, Augusto Esteves, Hugo Morais, Lucas Pereira

“…We analyzed the impact values provided by the Shapley additive explanation method when applied to two algorithms designed for tabular data—XGBoost and TabNet—and conducted a comprehensive evaluation of the overall model and across seasons. …”
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Interactive image segmentation algorithm based on adaptive kernel learning by LONG Jianwu, LI Jihao

“…Experimental results demonstrate that the proposed algorithm overperforms existing approaches across all evaluation metrics, achieving outstanding performance, and it validates the effectiveness and universality of the algorithm in handling complex scenarios.…”
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Corneal stromal mapping characteristics in normal corneas using anterior segment SD-OCT by Mohammad Abusamak, Mohammad Abusamak, Sara Mazen Issa, Amal F. Alomari, Husam A. Alsalamat, Husam A. Alsalamat, Nour S. Haj Ali, Abdallah Izmegna, Mais Shawashreh, Mahmoud Abu Samak, Talal M. Abusamak, Talal M. Abusamak

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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…This study developed a novel pixel-based grassland classification approach using three supervised machine learning (ML) algorithms, which were assessed in the province of Manitoba, Canada. …”
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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Experimental results show that the proposed algorithm increases MAP50 and MAP50.95 by 2.57% and 2.31%, respectively, compared to YOLOv8, while reducing parameter size and computational cost by 36.21% and 34.15%, respectively. …”
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Algorithmic Coverage Quantification and Visualization in Range-Free Sensor Networks by Maria S. Zakynthinaki, Ioannis S. Barbounakis, Emmanuel N. Antonidakis

“…Interactive satellite maps facilitate the dynamic exploration of coverage via the calculation and visualization of the resulting detection areas. …”
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Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

“…Lastly, we utilized a second-order Bezier curve to smoothen the path, eliminating sharp corners and discontinuities, ultimately yielding the optimal path. Across diverse map environments and two distinct dimensional scenarios, we conducted multiple sets of simulation experiments to validate the algorithm’s feasibility. …”
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Underwater Object Detection Algorithm Based on an Improved YOLOv8 by Fubin Zhang, Weiye Cao, Jian Gao, Shubing Liu, Chenyang Li, Kun Song, Hongwei Wang

“…Due to the complexity and diversity of underwater environments, traditional object detection algorithms face challenges in maintaining robustness and detection accuracy when applied underwater. …”
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HCRP-YOLO: A lightweight algorithm for potato defect detection by Haojie Liao, Guanping Wang, Siyu Jin, Yan Liu, Wei Sun, Sen Yang, Lu Wang

“…In recent years, deep-learning based object detection algorithms have gained significant attention in agriculture. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

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Long-Duration UAV Localization Across Day and Night by Fusing Dual-Vision Geo-Registration with Inertial Measurements by Xuehui Xing, Xiaofeng He, Ke Liu, Zhizhong Chen, Guofeng Song, Qikai Hao, Lilian Zhang, Jun Mao

“…To construct a cross-day-and-night localization system for long-duration UAVs, this study proposes a visual–inertial integrated localization system, where the visual component can register both RGB and infrared camera images in one unified VIS map. …”
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Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant. by María José Cambero Acosta, Guillermo de Anda-Jáuregui

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Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery by Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, Mihai Daniel Niţă

“…A sensitivity analysis across multiple spatial resolutions revealed that the performance of all algorithms varied significantly with changes in resolution, emphasizing the importance of selecting an appropriate scale for accurate forest mapping. …”
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Fast homozygosity mapping and identification of a zebrafish ENU-induced mutation by whole-genome sequencing. by Marianne L Voz, Wouter Coppieters, Isabelle Manfroid, Ariane Baudhuin, Virginie Von Berg, Carole Charlier, Dirk Meyer, Wolfgang Driever, Joseph A Martial, Bernard Peers

“…We generated 13 Gb of sequence, equivalent to an eightfold genomic coverage, from a pool of 50 mutant embryos obtained from a map-cross between the AB mutant carrier and the WIK polymorphic strain. …”
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Mapping hierarchical wetland characteristics by optical-SAR integration with collaborative spatial-spectral-temporal learning by Linwei Yue, Meiyue Wang, Chengpeng Huang, Qing Cheng, Qiangqiang Yuan, Huanfeng Shen

“…Inspired by the relationships of deep and shallow features, the intra-layer features are fused across the branches to generate the multi-level wetland mapping results (i.e., general wetland land cover, and wetland vegetation types). …”
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Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation by Alexander J. Sharp, Michael T. B. Pope, Andre Briosa e Gala, Richard Varini, Timothy R. Betts, Abhirup Banerjee

“…We apply the CDM inverse algorithm to both sets of reconstructions in order to compare derived conductions across various heart rhythms and AF conduction patterns. …”
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BSG-WSL: BackScatter-guided weakly supervised learning for water mapping in SAR images by Kai Wang, Zhongle Ren, Biao Hou, Weibin Li, Licheng Jiao

“…In BSG-WSL, a BackScatter-Guided Network (BSGNet) is proposed, where the backscatter information of water is used to guide the feature extraction process, yielding precise Class Attention Maps (CAMs) of water. Then, a morphological pseudo-label optimization algorithm is designed to employ CAMs to generate high-quality pseudo-labels. …”
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Mapping forest-agroforest frontiers in the Peruvian Amazon with deep learning and PlanetScope satellite data by Wanting Yang, Daniel Ortiz-Gonzalo, Xiaoye Tong, Dimitri Gominski, Rasmus Fensholt

“…Integrating a DEM as an additional helped the generalization of models across different geographical sites but did not improve the overall accuracy, whereas adding temporal information did not improve generalization or accuracy. …”
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Preliminary performance analysis using the PPP-RTK service of the National Land and Mapping Center in Taiwan by J.-Y. Lin, C.-H. Chu, F.-Y. Chu, K.-W. Chiang, M.-L. Tsai

“…The experimental equipment includes a tactical-grade Inertial Measurement Unit (IMU) and a low-cost receiver capable of receiving National Land Surveying and Mapping Center (NLSC) correction signals for PPP-RTK functionality. …”
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Mapping Mountain Permafrost via GPR-Augmented Machine Learning in the Northeastern Qinghai–Tibet Plateau by Yao Xiao, Guangyue Liu, Guojie Hu, Defu Zou, Ren Li, Erji Du, Tonghua Wu, Xiaodong Wu, Guohui Zhao, Yonghua Zhao, Lin Zhao

“…Thirteen classification algorithms were evaluated using 5-fold cross-validation repeated 40 times, with LightGBM, CatBoost, XGBoost, and RF achieving top performance (F1 > 0.98). …”
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