Improving Satellite Imagery Masking Using Multitask and Transfer Learning by Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons, Punwath Prum, Tamlin Pavelsky, John Gardner, Colin J. Gleason, Subhransu Maji

“…Many remote sensing applications require masking of pixels in satellite imagery for further analysis. …”
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Deep Learning Hybrid Architecture Based on Vision Transformer for Phase Analysis of Moiré Fringes by Dajie Yu, Junbo Liu, Chuan Jin, Yuyang Li, Kairui Zhang, Ji Zhou

“…This study offers valuable insights for expanding Moiré fringe imaging applications.…”
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A Black Box Doubly Fed Wind Turbine Electromechanical Transient Structured Model Fault Ride-Through Control Identification Method Based on Measured Data by Xu Zhang, Shenbing Ma, Jun Ye, Lintao Gao, Hui Huang, Qiman Xie, Liming Bo, Qun Wang

“…The results show that the method proposed in this paper has higher recognition accuracy and stronger robustness, and the recognition error is reduced by 2.89% compared with the traditional method, which is of high value for engineering applications.…”
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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

“…BaySurcls reduced root mean square error (RMSE) by an average of 20% in collocated scenarios, with reductions of up to 25% in highvariation sites. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The DNN framework significantly mitigates coastal salinity biases caused by RFI and land contamination, providing a robust tool for applications such as coastal hydrological monitoring and marine resource management.…”
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River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements by J. Marggraf, G. Dramais, J. Le Coz, B. Calmel, B. Camenen, D. J. Topping, W. Santini, G. Pierrefeu, F. Lauters

“…However, the uncertainty related to these measurements is rarely evaluated, as few studies of the major sources of error exist. Therefore, the aim of this study is to develop a method to determine the cross-sectional sand flux and estimate its uncertainty. …”
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International Survey on Phenylketonuria Newborn Screening by Domen Trampuž, Peter C. J. I. Schielen, Rolf H. Zetterström, Maurizio Scarpa, François Feillet, Viktor Kožich, Trine Tangeraas, Ana Drole Torkar, Matej Mlinarič, Daša Perko, Žiga Iztok Remec, Barbka Repič Lampret, Tadej Battelino, ISNS Study Group on PKU, Francjan J. van Spronsen, James R. Bonham, Urh Grošelj

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Evaluation of ECOSTRESS Collection 2 Evapotranspiration Products: Strengths and Uncertainties for Evapotranspiration Modeling by Zoe Amie Pierrat, Adam J. Purdy, Gregory Halverson, Joshua B. Fisher, Kanishka Mallick, Madeleine Pascolini‐Campbell, Youngryel Ryu, Martha C. Anderson, Claire Villanueva‐Weeks, Margaret C. Johnson, Brenna Hatch, Evan Davis, Yun Yang, Kerry Cawse‐Nicholson

“…We find the multi‐model ensemble achieves a root mean square error (RMSE) of 106 Wm−2 for instantaneous observations (reported as LE) and 1.2 mm day−1 for daily retrievals (reported as ET). …”
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Adaptive spatial-channel feature fusion and self-calibrated convolution for early maize seedlings counting in UAV images by Zhenyuan Sun, Zhenyuan Sun, Zhenyuan Sun, Zhi Yang, Zhi Yang, Yimin Ding, Yimin Ding, Boyan Sun, Boyan Sun, Saiju Li, Saiju Li, Zhen Guo, Zhen Guo, Lei Zhu, Lei Zhu

“…Traditional methods are labor-intensive and prone to errors. Unmanned Aerial Vehicle (UAV) technology offers a promising alternative; however, varying UAV altitudes can impact image quality, leading to blurred features and reduced accuracy in early maize seedling counts. …”
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Neuro-Musculoskeletal Modeling for Online Estimation of Continuous Wrist Movements from Motor Unit Activities by Yunfei Liu, Xu Zhang, Haowen Zhao, Xiang Chen, Bo Yao

“…Following offline model calibration with a global optimization algorithm, online angle estimation results demonstrated a significant superiority of the proposed model over the state-of-the-art NMS models (p &#x003C; 0.05), yielding the lowest normalized root mean square error (<inline-formula> <tex-math notation="LaTeX">$0.10~\pm ~0.02$ </tex-math></inline-formula>) and the highest determination coefficient (<inline-formula> <tex-math notation="LaTeX">$0.87~\pm ~0.06$ </tex-math></inline-formula>). …”
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Super-resolution reconstruction of the 1 arc-second Australian coastal DEM dataset by Bo Zhang, Zekai Shi, Danfeng Hong, Qi Wang, Jian Yang, Haoyuan Ren, Meng Zhang

“…Seafloor mapping to create a coastal DEM dataset of the oceans is significant for various applications. Land-based DEM monitoring and acquisition are more practical as compared to ocean DEM. …”
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ADEPNET: A Dynamic-Precision Efficient Posit Multiplier for Neural Networks by Aditya Anirudh Jonnalagadda, Uppugunduru Anil Kumar, Rishi Thotli, Satvik Sardesai, Sreehari Veeramachaneni, Syed Ershad Ahmed

“…This becomes especially useful for performing error-tolerant tasks like deep learning inference computation where low latency and area are a priority. …”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…Among the evaluated models, the RF model achieved the best performance, with a coefficient of determination (R²) of 0.895 and a root mean square error (RMSE) of 0.0058. A comparison with wheat orthophotos from the same period confirmed that the inversion results were highly consistent with actual growth conditions in the study area. …”
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Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context by Marcelo Bueno, Carlos Baca García, Nilton Montoya, Pedro Rau, Hildo Loayza

“…Statistical validation indicated suitable generalization error for scientific and practical use (RMSE < 0.05 cm3 cm-3). …”
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應用智慧型家教系統於國小學童閱讀策略 教學之學習歷程研究 A Study on the Learning Process of Applying an Autotutoring System to Teach Reading Strategies to Elementary School Children... by 陳茹玲 Ju-Ling Chen, 曾厚強 Hou-Chiang Tseng, 連啟舜 Chi-Shun Lien, 蔡旻穎 Min-Ying Tsai, 宋曜廷 Yao-Ting Sung

“…Future strategy instruction could incorporate demonstrations of self-assessment and error detection, supported by awareness scales that illustrate the effectiveness of comprehension monitoring. …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…UAVs are vastly used in practical applications such as reconnaissance and search and rescue or other missions which typically require experienced operators. …”
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Bayesian adaptation in Poisson cognitive systems by Aleksander A. Solodov

“…In particular, to describe the stochastic properties of cognitive systems and the possibility of creating an optimal algorithm, the Bayesian approach recognized in a number of philosophical works is applied.The optimal estimate by the criterion of the minimum standard error is, as is known, a posteriori mathematical expectation of a random estimated value, which is applied in this work. …”
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Automatic smart brain tumor classification and prediction system using deep learning by Qurat Ul Ain Ishfaq, Rozi Bibi, Abid Ali, Faisal Jamil, Yousaf Saeed, Rana Othman Alnashwan, Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna

“…The model’s precision, sensitivity, accuracy, f1-score, error rate, specificity, Y-index, balanced accuracy, geometric mean, and ROC are considered as performance metrics. …”
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Beyond the homozygous paradigm: symptomatic partial biotinidase deficiency in a heterozygous child—first case report from Nepal by Jagdish Kunwar, Bijay Kunwar, Anup Ghimire, Aramva Bikram Adhikari, Binay Aryal, Sachchu Thapa, Bina Prajapati Manandhar

“…Clinical trial number Not applicable.…”
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Aryana-bs: context-aware alignment of bisulfite-sequencing reads by Hassan Nikaein, Ali Sharifi-Zarchi, Afsoon Afzal, Saeedeh Ezzati, Farzane Rasti, Hamidreza Chitsaz, Govindarajan Kunde-Ramamoorthy

“…It outperforms existing methods, such as BSMAP, bwa-meth, Bismark, BSBolt, and abismal, particularly in robustness against genomic biases and alignment of longer, higher-error reads, demonstrating suitability for cancer research and cell-free DNA studies. …”
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