Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics by Félix Camirand Lemyre, Simon Lévesque, Marie-Pier Domingue, Klaus Herrmann, Jean-François Ethier

“…Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks. …”
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Forest classification and carbon stock estimation with integration of airborne LiDAR and satellite Gaofen-6 data in a subtropical region by Ruoqi Wang, Dengsheng Lu, Guiying Li, Yisa Li, Wenjing Liu

“…The inclusion of LCE variables consistently improved FCS estimation performance across all stratification schemes, while CHD-based stratification improved FSC estimation only when the LCE metrics were included. …”
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Plasticulture detection at the country scale by combining multispectral and SAR satellite data by Alessandro Fabrizi, Peter Fiener, Thomas Jagdhuber, Kristof Van Oost, Florian Wilken

“…We used cloud computing, freely available optical and radar satellite images, and machine learning to map plastic-mulched farmland (PMF) and plastic cover above vegetation (PCV) (e.g., greenhouse, tunnel) across Germany. …”
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SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…The experimental results show that the improved algorithm improves the <inline-formula> <tex-math notation="LaTeX">$mAP_{0.5}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$mAP_{0.5:0.95}$ </tex-math></inline-formula> metrics by 2.3% and 1.1%, respectively, on the VisDrone2019 benchmark dataset. …”
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Exploring suicidal thoughts among prospective university students: a study with applications of machine learning and GIS techniques by Mohammed A. Mamun, Firoj Al-Mamun, Md Emran Hasan, Nitai Roy, Moneerah Mohammad ALmerab, David Gozal, Md. Shakhaoat Hossain

“…Logistic regression analysis identified significant risk factors, while Machine Learning algorithms, including CatBoost and K-Nearest Neighbors, were used for prediction. …”
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BEV-CAM3D: A Unified Bird’s-Eye View Architecture for Autonomous Driving with Monocular Cameras and 3D Point Clouds by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…BEVCAM3D integrates a deformable cross-modality attention module for feature alignment and a fast ground segmentation algorithm to reduce computational overhead by 40%. …”
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Assessing water clarity in the Chesapeake Bay using satellite-derived Secchi disk depth by Seunghyun Son, Nikolay P. Nezlin, Veronica P. Lance

“…Satellite SDD maps from MODIS-Aqua and VIIRS-SNPP were generated using CB-SDD algorithm to analyze spatiotemporal variations of water clarity in the Chesapeake Bay. …”
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ETQ-Matcher: Efficient Quadtree-Attention-Guided Transformer for Detector-Free Aerial–Ground Image Matching by Chuan Xu, Beikang Wang, Zhiwei Ye, Liye Mei

“…We compare ETQ-Matcher to classic algorithms, and our experimental results demonstrate its superior performance in challenging aerial–ground urban scenes and multi-source remote sensing scenarios.…”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Multi-feature-based maritime radar target detection algorithms often rely on statistical models to accurately characterize sea clutter variations. …”
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Point Cloud Fusion of Human Respiratory Motion Under Multi-View Time-of-Flight Camera System: Voxelization Method Using 2D Voxel Block Index by Jiadun Wang, Shengtao Li, Kai Huang

“…Our algorithm first constructs a voxelized scene from multi-view depth maps. …”
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Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images by Gregory Starr, Sebastijan Mrak, Yukitoshi Nishimura, Michael Hirsch, Prakash Ishwar, Joshua Semeter

“…In this work, we develop a regularized inversion method for identifying the two dimensional structure of the MIT in Total Electron Content maps. Because no ground truth labels exist for the MIT, we extensively characterize the behavior of the algorithm by comparing it to the method developed by Aa, Zou, et al. (2020, doi:https://doi.org/10.1029/2019JA027583). …”
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Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework by Jinjiang Liu, Yonghua Xie, Yu Zhang, Haoming Li

“…To address these issues, this paper proposes a vehicle flow detection and tracking method that integrates an improved YOLOv8n model with the ByteTrack algorithm. In the detection module, we introduce the innovative MSN-YOLO model, which combines the C2f_MLCA module, the Detect_SEAM module, and the NWD loss function to enhance feature fusion and improve cross-scale information processing. …”
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Development and validation of trigger tools in primary care: A scoping review. by Inge Dhamanti, Elida Zairina, Ida Nurhaida, Salsabila Salsabila, Fitri Yakub

“…The sensitivity, specificity, and positive predictive value (PPV) of the final algorithm were critical in determining the validity of each trigger. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…The results demonstrate that YOLO-CS outperforms other algorithms, achieving a precision of 88.4%, a recall of 84.2%, and an mAP (mean average precision) of 92.1%. …”
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Improved printed circuit board defect detection scheme by Lufeng Bai, Wen Hao Xu

“…Compared to the original YOLOv8 algorithm, this algorithm improves the average accuracy on small targets by $$5.5\%$$ for mAP50.…”
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Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach by Lukas Zbinden, Samuel Erb, Damiano Catucci, Lars Doorenbos, Leona Hulbert, Annalisa Berzigotti, Michael Brönimann, Lukas Ebner, Andreas Christe, Verena Carola Obmann, Raphael Sznitman, Adrian Thomas Huber

“…Conclusion Automated quantification of liver mpMRI is highly effective across different patient populations, offering excellent reliability for total and segmental T1 and T2 maps. …”
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Unveiling the cell-type-specific landscape of cellular senescence through single-cell transcriptomics using SenePy by Mark A. Sanborn, Xinge Wang, Shang Gao, Yang Dai, Jalees Rehman

“…It is challenging to identify senescent cells because cellular senescence signatures and phenotypes vary widely across distinct cell types and tissues. Here we developed an analytical algorithm that defines cell-type-specific and universal signatures of cellular senescence across a wide range of cell types and tissues. …”
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Calculating slope gradient variations in the submarine landforms by R and Python statistical libraries by Polina Lemenkova

“…Such methods are proposed by R and Python programming languages that include libraries of machine learning algorithms for the data processing used in this research: {tidyverse}, {ggsignif}, {ggplot} and {magrittr} by R, StatsModels, Matplotlib, NumPy, Pandas and Seaborn by Python. …”
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A High-Resolution Gridded Dataset for China’s Monthly Sectoral Water Use by Yuqian Zhang, Yunhe Yin, Mijia Yin, Xufang Zhang

“…This algorithm disaggregates provincial annual water use data to monthly grid cells at a 0.1° × 0.1° resolution, enhancing the spatial detail and seasonal distribution of water use across China. …”
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Deep observations of the Type IIB flux landscape by A. Chauhan, M. Cicoli, S. Krippendorf, A. Maharana, P. Piantadosi, A. Schachner

“…Our algorithm is universally applicable across Calabi-Yau orientifold compactifications and can be used to enumerate flux vacua in a region given sufficient computational efforts. …”
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