Waterbody Detection and Reservoir Water Level Prediction Using Bayesian Mixture Models with Sentinel-1 GRD Data by DongHyeon Yoon, Ha-Eun Yu, Euiho Hwang, Ki-mook Kang, Gibeom Nam, Jin-Gyeom Kim

“…The mean absolute error values obtained validate the model’s capability to monitor water level fluctuations with a satisfactory degree of accuracy. …”
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Stress can be detected during emotion-evoking smartphone use: a pilot study using machine learning by Lydia Helene Rupp, Akash Kumar, Misha Sadeghi, Lena Schindler-Gmelch, Marie Keinert, Bjoern M. Eskofier, Bjoern M. Eskofier, Matthias Berking

“…XGBoost showed to be more reliable for prediction, with lower error for both training and test data.DiscussionThe findings provide further evidence that non-invasive video recordings can complement standard objective and subjective markers of stress.…”
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Deep learning model based on cascaded autoencoders and one‐class learning for detection and localization of anomalies from surveillance videos by Karishma Pawar, Vahida Attar

“…Assigning human personnel to continuously check the surveillance videos for finding suspicious activities such as violence, robbery, wrong U‐turns, to mention a few, is a laborious and error‐prone task. …”
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Tracking gain and loss of impervious surfaces by integrating continuous change detection and multitemporal classifications from 1985 to 2022 in Beijing by Xiao Zhang, Liangyun Liu, Wenhan Zhang, Linlin Guan, Ming Bai, Tingting Zhao, Zhehua Li, Xidong Chen

“…Specifically, we built dual continuous-change-detection models to pursue lower commission and omission errors for generating time-series training samples. …”
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Enhancing Fault Detection in Stochastic Environments Using Interval-Valued KPCA: A Cement Rotary Kiln Case Study by Abdelhalim Louifi, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Abderazak Bensmail, Majdi Mansouri

“…Fault detection in industrial processes is challenging due to significant data uncertainty, which complicates the accurate modeling of interval-valued data and the quantification of errors necessary for reliable detection. …”
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Evaluating the Effectiveness of Artificial Intelligence in Prostate Cancer Detection using Biparametric Magnetic Resonance Imaging: A Comparative Study by Rossy Vlăduţ TEICĂ, Ioana Andreea GHEONEA

“…Error distribution included 36% false-negative findings, 21% false-positive findings, 20% PI-RADS (Prostate Imaging-Reporting and Data System) overestimations, and 23% PI-RADS underestimations. …”
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Pengolahan Citra Berbasis Video Proccesing dengan Metode Frame Difference untuk Deteksi Gerak by Yovi Apridiansyah, Ardi Wijaya, Pahrizal, Rozali Toyib, Arif Setiawan

“…The test results obtained 16 out of 20 test data that were successfully detected correctly (True Positive), there were 2 test data that resulted in a False Positive error, and 2 test data that resulted in a False Negative error. …”
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Outlier Traffic Flow Detection and Pattern Analysis Under Unplanned Disruptions: A Low-Rank Robust Decomposition Model by Zhipeng Duan

“…Outlier traffic flow detection under unplanned disruptions is vital for operational safety and management. …”
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models by Ayub Mohammadi, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, Nadhir Al-Ansari

“…Findings showed that root mean square error was 0.31 and 0.3 for ADTree and bag-ADTree techniques, respectively. …”
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Enhanced Leakage Detection and Estimation via a Hybrid Genetic Algorithm and High-Order Sliding Modes Observer Approach by David Pumaricra-Rojas, Gustavo Perez-Zuniga, Javier Sotomayor-Moriano

“…A parameterized model based on momentum and mass balance equations with discretization is used, where the parameters are the location and magnitude of the leakage. To find these parameters, it incorporates the Genetic Algorithm to solve an optimization problem that relies on a function cost related to the error norm between measurements and states estimation from HOSMO in order to measure the difference between the model with an assumed leakage and the real leakage. …”
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Integration of YOLOv8 Small and MobileNet V3 Large for Efficient Bird Detection and Classification on Mobile Devices by Axel Frederick Félix-Jiménez, Vania Stephany Sánchez-Lee, Héctor Alejandro Acuña-Cid, Isaul Ibarra-Belmonte, Efraín Arredondo-Morales, Eduardo Ahumada-Tello

“…However, conventional identification techniques used by biologists are time-consuming and susceptible to human error. The integration of deep learning models offers a promising alternative to automate and enhance species recognition processes. …”
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OGLE-2016-BLG-1195Lb: A Sub-Neptune Beyond the Snow Line of an M-dwarf Confirmed by Keck Adaptive Optics by Aikaterini Vandorou, Lisa Dang, David P. Bennett, Naoki Koshimoto, Sean K. Terry, Andrzej Udalski, Jean-Philippe Beaulieu, Christophe Alard, Aparna Bhattacharya, Joshua W. Blackman, Ian A. Bond, Tarik Bouchoutrouch-Ku, Andrew A. Cole, Nicolas B. Cowan, Jean-Baptiste Marquette, Clément Ranc, Natalia E. Rektsini, Sylvain Cetre, Jim Lyke, Eduardo Marin, Peter Wizinowich

“…We find that we cannot confidently recover the same detrended light curve that is likely dominated by systematic errors in the photometric data. …”
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Toward automated plantar pressure analysis: machine learning-based segmentation and key point detection across multicenter data by Carlo Dindorf, Jonas Dully, Steven Simon, Dennis Perchthaler, Stephan Becker, Hannah Ehmann, Christian Diers, Christoph Garth, Michael Fröhlich

“…Furthermore, regression-based approaches generated higher errors in key point detection of the interdigital space 2–3 (Median Euclidean distance = 10.06) than in metatarsal area 1 center (Median Euclidean distance = 7.72). …”
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Bottom Plate Damage Localization Method for Storage Tanks Based on Bottom Plate-Wall Plate Synergy by Yunxiu Ma, Linzhi Hu, Yuxuan Dong, Lei Chen, Gang Liu

“…The maximum relative localization error was measured as 5.4%, indicating superior detection accuracy.…”
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Development of a collision avoidance system for agricultural airboat based on laser sensor by LIU Yufei, HE Yong, NOGUCHI Noboru

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Detection of Remaining Feed in the Feed Troughs of Flat-Fed Meat Ducks Based on the RGB-D Sensor and YOLO V8 by Xueliang Tan, Junjie Yuan, Shijia Ying, Jizhang Wang

“…Analyses of the correction coefficients and corresponding RMSE values indicated a positive correlation between the correction coefficient and the curvature of the feeding trough, while no correlation was observed with the trough diameter or granule particle size, maintaining a low RMSE value. The findings of this research demonstrate the effectiveness of the proposed method for detecting the remaining feed in troughs. …”
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Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection. by Ekramul Haque Tusher, Mohd Arfian Ismail, Abdullah Akib, Lubna A Gabralla, Ashraf Osman Ibrahim, Hafizan Mat Som, Muhammad Akmal Remli

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Enhancing Multi-Flight Unmanned-Aerial-Vehicle-Based Detection of Wheat Canopy Chlorophyll Content Using Relative Radiometric Correction by Jiale Jiang, Qianyi Zhang, Shuai Gao

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Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo, Jianying Sun

“…Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. …”
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A Method for Real-Time Vessel Speed Measurement Based on M-YOLOv11 and Visual Tracking by Zhe Ma, Qinyou Hu, Yuezhao Wu, Wei Wang

“…Over 60% of the measured vessel speed measurement errors are less than 0.5 knots, with an overall average error below 0.45 knots. …”
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