On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…</p> <p>The generated patterns of global ET variability were relatively consistent across the ML models overall, but in regions with low data support via eddy covariance (EC) stations, we observed substantial biases across models and covariate setups and large ensemble uncertainties. …”
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Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index by Stephan Kemenes, Stephan Kemenes, Liu Chang, Maja Schlereth, Rita Noversa de Sousa, Rita Noversa de Sousa, Ioanna Minopoulou, Pauline Fenzl, Pauline Fenzl, Giulia Corte, Giulia Corte, Melek Yalcin Mutlu, Melek Yalcin Mutlu, Michael Wolfgang Höner, Michael Wolfgang Höner, Ioannis Sagonas, Ioannis Sagonas, Birte Coppers, Birte Coppers, Anna-Maria Liphardt, Anna-Maria Liphardt, David Simon, Arnd Kleyer, Lukas Folle, Michael Sticherling, Michael Sticherling, Georg Schett, Georg Schett, Andreas Maier, Filippo Fagni, Filippo Fagni

“…A reader study was performed to assess inter-rater variability.ResultsIn total, 460 patients providing 4,400 nail photographs were included in the training dataset. …”
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Comparison of Surgical Outcomes between Endovenous Laser Ablation and Conventional Surgery in Patients with Lower Limb Varicose Veins: A Prospective Interventional Study by Mannam Viswateja, Deepak R Chavan, Vijaya Patil, Vikram U Sindagikar

“…Introduction: Dilated, convoluted, subcutaneous veins measuring more than 3 mm in diameter when measured while upright and exhibiting reflux are called varicose veins. …”
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GRU2-Net: Global response double U-shaped network for lesion segmentation in ultrasound images by Xiaokai Jiang, Xuewen Ding, Jinying Ma, Chunyu Liu, Xinyi Li

“…To improve global context modeling, this paper proposes the Global Response Transformer Block in the bottleneck, enabling the network to capture long-range dependencies and structural variability in lesion appearance. By modeling interactions across distant regions, the block more effectively captures the variability in lesion shape, size, and location, enhancing segmentation accuracy for complex and irregular structures in ultrasound images. …”
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Long Term Predictability of Southern Ocean Surface Nutrients Using Explainable Neural Networks by Gian Giacomo Navarra, Curtis Deutsch, Antonios Mamalakis, Andrew Margolskee, Graeme MacGilchrist

“…Abstract The Southern Ocean is a region of high surface nutrient content, reflecting an inefficient biological carbon pump. The variability, predictability, and causes of changes in these nutrient levels on interannual to decadal time scales remain unclear. …”
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CDSE-UNet: Enhancing COVID-19 CT Image Segmentation With Canny Edge Detection and Dual-Path SENet Feature Fusion by Jiao Ding, Jie Chang, Renrui Han, Li Yang

“…Moreover, we have developed a Multiscale Convolution Block (MSCovBlock), replacing the standard convolution in UNet, to adapt to the varied lesion sizes and shapes. …”
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A multimodal functional structure-based graph neural network for fatigue detection by Dongrui Gao, Zhihong Zhou, Zongyao Peng, Haokai Zhang, Shihong Liu, Manqing Wang, Hongli Chang

“…An innovative intra- and inter-channel separable convolution module is designed to extract deep interaction patterns through parallel convolution operations within and across signal channels. …”
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Hyperspectral segmentation of plants in fabricated ecosystems by Petrus H. Zwart, Petrus H. Zwart, Petrus H. Zwart, Peter Andeer, Trent R. Northen

“…To further enhance robustness, we incorporate image alignment techniques to address spatial variability in the dataset. Downstream analysis focuses on using the segmented data for processing spectral data, enabling monitoring of plant health. …”
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Comparative Study of the Performance of Two Treatment Planning Systems Using Tests from the MPPG 5b Guidelines, TECDOC 1583 and Venselaar's Confidence Limits by Carlos Vega D'Espaux, Federico Lorenzo, Franco La Paz Mastandrea, Nicolás Larragueta

“…The methodologies recommended by Venselaar, the MPPG 5b protocol by the American Association of Physicists in Medicine (AAPM), and the guidelines of the IAEA TECDOC 1583 for heterogeneity assessment were adopted for this purpose.The results indicated that the Eclipse™ system showed better overall performance in water measurements, with lower variability and greater compliance with gamma criteria (average above 95% in 3%, 2 mm profile tests). …”
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Application of Atmospheric Gases and Particulate Matter to the Assessment of Urban Heat Island by Christian Mark Salvador, Pablo Fernandez, Kelsey Carter, Joanna Tannous, David Weston, Christopher DeRolph, Melanie A. Mayes

“…Objectives This study aims to utilize the variability of atmospheric components such as particulate matter (PM), inorganic gases, and volatile organic compounds (VOCs) as direct tracers of the degree of urbanization for ground-based measurements to fully comprehend UHI in convoluted regions with indistinct delineation of urban and nonurban environments. …”
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Toward the validation of crowdsourced experiments for lightness perception. by Emily N Stark, Terece L Turton, Jonah Miller, Elan Barenholtz, Sang Hong, Roxana Bujack

“…Here, we propose that the error due to a crowdsourced experimental design can be effectively averaged out because the crowdsourced experiment can be accommodated by the Thurstonian model as the convolution of two normal distributions, one that is perceptual in nature and one that captures the error due to variability in stimulus presentation. …”
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Linguistic-visual based multimodal Yi character recognition by Haipeng Sun, Xueyan Ding, Zimeng Li, Jian Sun, Hua Yu, Jianxin Zhang

“…Abstract The recognition of Yi characters is challenged by considerable variability in their morphological structures and complex semantic relationships, leading to decreased recognition accuracy. …”
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A Robust Hybrid CNN+ViT Framework for Breast Cancer Classification Using Mammogram Images by Vasudha Rani Patheda, Gunda Laxmisai, B. V. Gokulnath, S. P. Siddique Ibrahim, S. Selva Kumar

“…This research addresses the variability and potential oversight in radiologists&#x2019; manual mammogram interpretations, aiming to enhance classification accuracy by combining Convolution Neural Networks (CNNs) and Vision Transformers (ViTs). …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The complexity and variability of real-world road environments make the detection of densely occluded objects more challenging in autonomous driving scenarios. …”
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Gitelman Syndrome: A Rare Cause of Seizure Disorder and a Systematic Review by Muhammad Asim Shahzad, Maryam Mukhtar, Asrar Ahmed, Waqas Ullah, Rehan Saeed, Mohsin Hamid

“…It is caused by tubular defects at the level of distal convoluted tubules, mimicking a thiazide-like tumor. …”
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CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland by B. Kraft, M. Schirmer, W. H. Aeberhard, M. Zappa, S. I. Seneviratne, L. Gudmundsson

“…We test two sequential deep-learning architectures: a long short-term memory (LSTM) model, which is a recurrent neural network able to learn complex temporal features from sequences, and a convolution-based model, which learns temporal dependencies via 1D convolutions in the time domain. …”
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Distinguishable IQ Feature Representation for Domain-Adaptation Learning of WiFi Device Fingerprints by Abdurrahman Elmaghbub, Bechir Hamdaoui

“…., day/time, location, channel, etc.) changes and variability. This work proposes a novel IQ data representation and feature design, termed Double-Sided Envelope Power Spectrum or <monospace>EPS</monospace>, that is proven to significantly overcome the domain adaptation challenges associated with WiFi transmitter fingerprinting. …”
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Identification of Low‐Value Defects in Infrared Images of Porcelain Insulators Based on STCE‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Keyu Li, Haichao Sun, Mianxiao Wu, Bo Lan

“…And the multiple attention mechanism improved to the third generation of variability convolution is used to detect the head to improve the accuracy of the algorithm's target localization. …”
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The best angle correction of basketball shooting based on the fusion of time series features and dual CNN by Meicai Xiao

“…However, the current method is limited by the variability of the shape base, ignoring dynamic features and visual information, and there are some problems in the process of feature extraction and correction of related actions. …”
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Biological features and medical significance of the <i>Listeria</i> bacteria by I. A. Derevyanchenko, Lyudmila A. Kraeva

“…The increasing role of Listeria in the pattern of human and animal infectious pathologies, the variability of their morphological, cultivable and biochemical properties, as well as the constant modification of the surface Listeria antigens underlies a need to improve listeriosis diagnostics and requires creation of new immunobiological preparations and modern regimens for isolation and identification of various Listeria types. …”
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