Baseline high-resolution maps of soil nutrients in Morocco to support sustainable agriculture by Yassine Bouslihim, Abdelkrim Bouasria, Ahmed Jelloul, Lotfi Khiari, Sara Dahhani, Rachid Mrabet, Rachid Moussadek

“…This paper presents the first national reference maps of available P and exchangeable K at 250 m resolution over Morocco’s croplands using digital soil mapping with machine learning algorithms and environmental covariates. …”
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Understanding Information Propagation in Online Social Networks: A Systematic Mapping Study by Eleana Jerez-Villota, Francisco Jurado, Jaime Moreno-Llorena

“…The work presented in this article aims to analyse the state of the art on IP in OSNs, mapping the models, methods, algorithms, tools, and techniques developed in this domain. …”
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Enhancing Reliability in Redundant Homogeneous Sensor Arrays with Self-X and Multidimensional Mapping by Elena Gerken, Andreas König

“…This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems.…”
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Adversarial patch defense algorithm based on PatchTracker by Zhenjie XIAO, Shiyu HUANG, Feng YE, Liqing HUANG, Tianqiang HUANG

“…The application of deep neural networks in target detection has been widely adopted in various fields.However, the introduction of adversarial patch attacks, which add local perturbations to images to mislead deep neural networks, poses a significant threat to target detection systems based on vision techniques.To tackle this issue, an adversarial patch defense algorithm based on PatchTracker was proposed, leveraging the semantic differences between adversarial patches and image backgrounds.This algorithm comprised an upstream patch detector and a downstream data enhancement module.The upstream patch detector employed a YOLOV5 (you only look once-v5) model with attention mechanism to determine the locations of adversarial patches, thereby improving the detection accuracy of small-scale adversarial patches.Subsequently, the detected regions were covered with appropriate pixel values to remove the adversarial patches.This module effectively reduced the impact of adversarial examples without relying on extensive training data.The downstream data enhancement module enhanced the robustness of the target detector by modifying the model training paradigm.Finally, the image with removed patches was input into the downstream YOLOV5 target detection model, which had been enhanced through data augmentation.Cross-validation was performed on the public TT100K traffic sign dataset.Experimental results demonstrated that the proposed algorithm effectively defended against various types of generic adversarial patch attacks when compared to situations without defense measures.The algorithm improves the mean average precision (mAP) by approximately 65% when detecting adversarial patch images, effectively reducing the false negative rate of small-scale adversarial patches.Moreover, compared to existing algorithms, this approach significantly enhances the accuracy of neural networks in detecting adversarial samples.Additionally, the method exhibited excellent compatibility as it does not require modification of the downstream model structure.…”
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Speech Enhancement Algorithms: A Systematic Literature Review by Sally Taha Yousif, Basheera M. Mahmmod

“…A growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. …”
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Particle algorithms for animal movement modelling in receiver arrays by Edward Lavender, Andreas Scheidegger, Carlo Albert, Stanisław W. Biber, Janine Illian, James Thorburn, Sophie Smout, Helen Moor

“…We find the particle smoothing methodology outperforms heuristic methods across the board. Particle‐based maps represent simulated movements more accurately, even in dense receiver arrays, and are better suited to analyses of home ranges, residency and habitat preferences. …”
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MRI R2* and quantitative susceptibility mapping in brain tissue with extreme iron overload by Christoph Birkl, Marlene Panzer, Christian Kames, Anna Maria Birkl-Toeglhofer, Alexander Rauscher, Bernhard Glodny, Elke R. Gizewski, Heinz Zoller

“…Results R2* values varied significantly across algorithms, particularly in the putamen (F(5,50) = 16.51, p < 0.001). …”
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Learning Condition-Invariant Scene Representations for Place Recognition across the Seasons Using Auto-Encoder and ICA by Tariqul Islam, Sheikh Rabiul Islam, Mahbubur Rahman

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UAVs-Based Visual Localization via Attention-Driven Image Registration Across Varying Texture Levels by Yan Ren, Guohai Dong, Tianbo Zhang, Meng Zhang, Xinyu Chen, Mingliang Xue

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Accurate Paddy Rice Mapping Based on Phenology-Based Features and Object-Based Classification by Jiayi Zhang, Lixin Gao, Miao Liu, Yingying Dong, Chongwen Liu, Raffaele Casa, Stefano Pignatti, Wenjiang Huang, Zhenhai Li, Tingting Tian, Richa Hu

“…However, high-quality rice mapping products at high resolutions are still scarce around the Inner Mongolia Autonomous Region. …”
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Integrating Landsat, Sentinel-2 and Sentinel-1 time series for mapping intermediate crops by Kassandra Jensch, Gohar Ghazaryan, Stefan Ernst, Patrick Hostert, Claas Nendel

“…Here, we propose a classification algorithm that combines field data, satellite imagery from multiple optical sensors and synthetic-aperture radar (SAR) data to map intermediate crops across Brandenburg, Germany. …”
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A robust approach to satellite image encryption using chaotic map and circulant matrices by Shamsa Kanwal, Saba Inam, Asghar Ali Shah, Halima Iqbal, Anas Bilal, Muhammad Usman Hashmi, Raheem Sarwar

“…The algorithm initiates with computing alterations by a shift amount. …”
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Unmanned Aerial Vehicles Applicability to Mapping Soil Properties Under Homogeneous Steppe Vegetation by Azamat Suleymanov, Mikhail Komissarov, Mikhail Aivazyan, Ruslan Suleymanov, Ilnur Bikbaev, Arseniy Garipov, Raphak Giniyatullin, Olesia Ishkinina, Iren Tuktarova, Larisa Belan

“…We estimated the models using a cross-validation approach and spatial prediction uncertainties. …”
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Integrating GIS and remote sensing for soil attributes mapping in degraded pastures of the Brazilian Cerrado by Rômullo Oliveira Louzada, Ivan Bergier, Édson Luis Bolfe, Jayme Garcia Arnal Barbedo

“…Elevation and GLCM metrics emerged as key predictors across depths. These findings highlight the effectiveness of integrating diverse remote sensing data with ML for soil attributes mapping, particularly for clay and CEC.…”
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Visual navigation and crop mapping of a phenotyping robot MARS-PhenoBot in simulation by Zhengkun Li, Rui Xu, Changying Li, Longsheng Fu

“…Additionally, a field mapping workflow based on RTAB-MAP (Real-Time Appearance-Based Mapping) and V-SLAM (Visual Simultaneous Localization and Mapping) was developed. …”
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Mapping and quantifying deforestation in the Zambezi ecoregion of Central-Southern Africa: extent and spatial structure by Héritier Khoji Muteya, Héritier Khoji Muteya, Dieu-donné N’tambwe Nghonda, Dieu-donné N’tambwe Nghonda, François Malaisse, Jan Bogaert, Yannick Useni Sikuzani

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Bridge Crack Segmentation Algorithm Based on Improved U-Net by Yanhao Fang, Jie LYu, Yonghua Xia, Yingke Wang

“…Experimental results show that it outperforms other algorithms in accuracy and improves upon the original U-Net across all metrics, with mIoU (Mean Intersection over Union) and F1-Score increasing by 1.23% and 1.89%, respectively.…”
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Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing by Xinle Zhang, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, Xiaomeng Zhu

“…These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. …”
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Spatiotemporal Analysis of Soil Moisture Variability and Precipitation Response Across Soil Texture Classes in East Kazakhstan by Dmitry Chernykh, Roman Biryukov, Andrey Bondarovich, Lilia Lubenets, Anatoly Pavlenko, Kamilla Rakhymbek, Denis Revenko, Zheniskul Zhantassova

“…This study analyzed soil moisture within the root zone (0–28 cm depth). A JavaScript-based algorithm was developed in Google Earth Engine to analyze soil moisture and total precipitation across five Soil Texture Index categories during the growing seasons (April–September) of 2013, 2022, and 2023. …”
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Cloud Removal Algorithm by Combining MODIS and VIIRS Snow Products by Xiaoyan Wang, Shi Liang, Yanlong Shen, Hui Guo, Zhiqi Ouyang

“…However, differences in cloud identification algorithms lead to significant discrepancies in cloud and snow distribution between MODIS and VIIRS snow products. …”
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