Improve unsupervised Learning-based landslides detection by band ratio processing of RGB optical images: a case study on rainfall-induced landslide clusters by Lichuan Chen, Xuekun Xiang, Haijia Wen, Jiafeng Xiao, Chenhao Song, Xinzhi Zhou, Jingyuan Yu

“…Finally, the causes of missing and errors in landslide detection by using the two methods are analyzed and discussed. …”
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Uniform Quantization for Multi-Antenna Amplify–Quantize–Forward Relay by Gangsan Jeong, Xianglan Jin

“…To address this, we evaluate error performance at the destination for the entire AQF relay communication system by introducing a linear detection method with significantly reduced complexity in the MIMO AQF relay channel. …”
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The evolution of eavesdropping on heterospecific alarm calls: Relevance, reliability, and personal information by Cameron Rouse Turner, Matt Spike, Robert D. Magrath

“…This is because senders trade‐off false alarms and missed predator detections in a way that is also favorable for the eavesdropper, by producing less of the costlier error. …”
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Power Assessment and Performance Comparison of Wind Turbines Driven by Multivariate Environmental Factors by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou, Zhao Rao, Haoxuan Luo, Weihao Ji

“…The proposed method achieves substantial improvements in predictive accuracy, with decreases of 9.39% in mean absolute error (MAE) and 11.75% in root mean square error (RMSE), compared to conventional binning approaches. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…As fifth-generation (5G) and next-generation communication systems advance and find widespread application in critical infrastructures, the importance of vulnerability detection becomes increasingly critical. …”
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Grapevine inflorescence segmentation and flower estimation based on Computer Vision techniques for early yield assessment by Germano Moreira, Filipe Neves dos Santos, Mário Cunha

“…The models demonstrated a strong correlation (R2 > 90.0%) between detected and visible flowers in inflorescences. A statistical analysis confirmed the robustness of the framework, with the YOLOv8 model once again standing out, showing no significant differences in error rates across diverse grapevine morphologies and varieties, ensuring wide applicability. …”
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Fractal Algorithm for Multiple-lens Analyses by F. Abe

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Decision tree for severity assessment of neurodegenerative diseases using possibility approach and gait dynamics by Preeti Khera, Ashok Kumar, Rajat Kapila

“…The proposed framework achieved a high coefficient of determination (R2 ≈ 0.90) and low error rates with stratified 10-fold cross-validation. …”
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Prediction of Winter Wheat Yield and Interpretable Accuracy Under Different Water and Nitrogen Treatments Based on CNNResNet-50 by Donglin Wang, Yuhan Cheng, Longfei Shi, Huiqing Yin, Guangguang Yang, Shaobo Liu, Qinge Dong, Jiankun Ge

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A SERS Sensor Prepared via Electrostatic Self-Assembly of Ta₄C₃@AgNP Nanocomposites for Detection of Ziram by Kai Hua, Liang Li, Pei Liang

“…When different test areas are selected, the relative error of intensity under the same wave number is less than 10.7%, showing good repeatability and consistency. …”
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Detecting soil-transmitted helminth and Schistosoma mansoni eggs in Kato-Katz stool smear microscopy images: A comprehensive in- and out-of-distribution evaluation of YOLOv7 varian... by Mohammed Aliy Mohammed, Esla Timothy Anzaku, Peter Kenneth Ward, Bruno Levecke, Janarthanan Krishnamoorthy, Wesley De Neve, Sofie Van Hoecke

“…Additionally, we used the Toolkit for Identifying object Detection Errors (TIDE) and Gradient-weighted Class Activation Mapping (Grad-CAM) to perform a comprehensive analysis of the results.…”
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Point-of-care diagnostics and resistance phenotyping to combat ash dieback by Pierluigi Bonello, Anna O. Conrad, Dušan Sadiković, Mateusz Liziniewicz, Michelle Cleary

“…We also show that the same approach can be used to identify disease-resistant European ash accessions based on data from two independent, multiyear clonal trials, with a testing error rate of 0.155. These results confirm that NIR spectroscopy combined with machine learning is sensitive enough for early disease detection and resistance screening in this system. …”
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Personalized Contextual Information Delivery Using Road Sign Recognition by Byungjoon Kim, Yongduek Seo

“…Experimental results show that the proposed system achieves a 23.4% increase in user-adapted information accuracy and reduces interpretation errors by 17.8% in real-world navigation scenarios. …”
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Deep Learning for Ore Haulage Monitoring: Vibrational Analysis Using a VGG16 Network by Artur Skoczylas, Pawel Stefaniak, Sergii Anufriiev, Wioletta Koperska

“…Automated detection of work cycles in underground ore haulage is crucial for optimizing operational efficiency and minimizing costs, yet existing methods often rely on manual logging or basic telematics, which can be inefficient and prone to errors. …”
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A vision model for automated frozen tuna processing by Richeng Wang, Xiongsheng Zheng, Yan Chen

“…These findings highlight TunaVision’s effectiveness in segmenting, detecting, and estimating poses of frozen tuna, offering valuable insights for the development of automated processing systems.…”
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Performance and Scalability of Data Cleaning and Preprocessing Tools: A Benchmark on Large Real-World Datasets by Pedro Martins, Filipe Cardoso, Paulo Váz, José Silva, Maryam Abbasi

“…We benchmark each tool on dataset sizes ranging from 1 million to 100 million records, measuring execution time, memory usage, error detection accuracy, and scalability under increasing data volumes. …”
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Experimental Study on Microseismic Monitoring of Depleted Reservoir-Type Underground Gas Storage Facility in the Jidong Oilfield, North China by Yuanjian Zhou, Cong Li, Hao Zhang, Guangliang Gao, Dongsheng Sun, Bangchen Wu, Chaofeng Li, Nan Li, Yu Yang, Lei Li

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Quantitative determination of blended proportions in tobacco formulations using near-infrared spectroscopy and transfer learning by Qinlin Xiao, Qinlin Xiao, Ruifang Gu, Li Li, Jing Wen, Xixiang Zhang, Yi Shen, Yang Liu, Lan Xiao, Qinqin Tang, Jun Yang, Yong He, Juan Yang

“…Accurate detection of blending proportions in tobacco formulations is crucial for ensuring the quality consistency and flavor stability of cigarette products. …”
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Back Propagation Neural Network model for analysis of hyperspectral images to predict apple firmness by Shuiping Li, Yueyue Chen, Xiaobo Zhang, Junbo Wang, Xuanxiang Gao, Yunhong Jiang, Zhaojun Ban, Cunkun Chen

“…The coefficient of determination (R2) and root mean square error (RMSE) of Partial Least Squares (PLS) models are contrasted using various inputs. …”
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Impact of Parameters and Tree Stand Features on Accuracy of Watershed-Based Individual Tree Crown Detection Method Using ALS Data in Coniferous Forests from North-Eastern Poland by Marcin Kozniewski, Łukasz Kolendo, Szymon Chmur, Marek Ksepko

“…Consequently, adjusting the pixel size of a canopy height model in the context of tree stand features is necessary to minimize error. Additionally, our findings show that there is a need to carefully assess the criterion of membership of a detected tree crown in a circular sample plot, which we based on the point cloud.…”
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