Spatiotemporal hybrid deep learning for estimating and analyzing carbon stocks: a case study in Jiangsu province, China by Lizhi Miao, Jvmin Wang, Kaiwen Wu, Heng Xu, Xiying Sun, Gang Lu, Mei-Po Kwan

“…The model demonstrated excellent performance in predicting carbon (R2 = 0.91, 10-fold CV R2 = 0.80). …”
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Use of Vision Transformer to Classify Sea Surface Phenomena in SAR Imagery by Junfei Xia, Roland Romeiser, Wei Zhang, Tamay Ozgokmen

“…Notably, this study introduces the use of the attention mechanism in ViTs to elucidate model decision-making, providing interpretability by highlighting regions that influence predictions and revealing why the model succeeds or fails in specific cases. …”
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Future Dynamics of Drought in Areas at Risk: An Interpretation of RCP Projections on a Regional Scale by Pietro Monforte, Sebastiano Imposa

“…Data were aggregated on a 0.50° × 0.50° spatial grid and bias-corrected using linear scaling. …”
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The roles of surface processes in porphyry copper deposit preservation by B. Hadler Boggiani, T. Salles, C. Mallard, N. Atwood

“…While our landscape evolution model successfully predicts the known emplacement depths for the North and South Andean deposits younger than 20 <span class="inline-formula">Myr</span>, it also predicts depths exceeding 6 <span class="inline-formula">km</span> for Central Andean deposits older than 60 <span class="inline-formula">Myr</span>. …”
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Tree species classification using intensity patterns from individual tree point clouds by Andreas Tockner, Ralf Kraßnitzer, Christoph Gollob, Sarah Witzmann, Tim Ritter, Arne Nothdurft

“…However, recent studies assessing tree species labels on single tree point clouds have been insufficiently accurate in complex forest ecosystems; moreover, explainability of machine-learning methods used in published studies has been insufficient. Whether the predictions of black-box models suffer from over-fitting or whether they are based on characteristic species traits often remains unclear. …”
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Skin-Inspired Magnetoresistive Tactile Sensor for Force Characterization in Distributed Areas by Francisco Mêda, Fabian Näf, Tiago P. Fernandes, Alexandre Bernardino, Lorenzo Jamone, Gonçalo Tavares, Susana Cardoso

“…The spatial sensitivity model was trained on 171,008 points and achieved a mean absolute error of 0.26 mm when predicting the location of applied force within a sensitive area of 25.5 mm × 25.5 mm using sensors spaced 4.5 mm apart. …”
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YO-AFD: an improved YOLOv8-based deep learning approach for rapid and accurate apple flower detection by Dandan Wang, Dandan Wang, Huaibo Song, Huaibo Song, Huaibo Song, Bo Wang

“…The timely and accurate detection of apple flowers is crucial for assessing the growth status of fruit trees, predicting peak blooming dates, and early estimating apple yields. …”
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Enhancing Deep Learning Sustainability by Synchronized Multi Augmentation with Rotations and Multi-Backbone Architectures by Nikita Gordienko, Yuri Gordienko, Sergii Stirenko

“…The outputs provided by these MBs are merged through different fusion strategies: Averaging Fusion with aggregation of predictions and Dense Fusion with integration of features via a fully connected neural network. …”
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Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

“…This comparison underscores the model’s robustness, highlighting improvements in minimizing false positives and false negatives, which are crucial for real-world applications where reliable predictions are essential. …”
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TraxVBF: A hybrid transformer-xLSTM framework for EMG signal processing and assistive technology development in rehabilitation by Seyyed Ali Zendehbad, Athena Sharifi Razavi, Marzieh Allami Sanjani, Zahra Sedaghat, Saleh Lashkari

“…This allows the model to predict movement trajectories accurately, enabling motor learning and functional recovery of patients through real time feedback without the expensive hardware. …”
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Radial Flow Component of Sun’s High-frequency Retrograde Inertial Waves by Chris S. Hanson, Vivek Menon, Shravan Hanasoge, Katepalli R. Sreenivasan

“…We demonstrate that this signal is indeed part of the HFR modes and not spatial leakage from prograde flows associated with magnetic regions. …”
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Risk analysis of distribution network outages under a typhoon–rainstorm–flood disaster chain by Hui Hou, Wenjie Wu, Ruizeng Wei, Huan He, Lei Wang, Zhengtian Li, Xiangning Lin

“…Second, a one‐dimensional pipe network and a two‐dimensional surface‐coupled urban flood model are constructed to predict flood depth based on the typhoon–rainstorm time series. …”
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Development of a Digital Hologram Map Using Bathymetric Data by Jumamurod Farhod Ugli Aralov, Oybek Mirzaevich Narzulloev, Leehwan Hwang, Philippe Gentet, Seunghyun Lee

“…Most traditional bathymetric mapping techniques rely on two-dimensional representations, which require users to mentally infer depth and spatial relationships. This cognitive burden can lead to misinterpretation, particularly when analyzing complex seafloor structures with subtle variations. …”
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Integration of Drone and Satellite Imagery Improves Agricultural Management Agility by Michael Gbenga Ogungbuyi, Caroline Mohammed, Andrew M. Fischer, Darren Turner, Jason Whitehead, Matthew Tom Harrison

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C-Band Radar-Based Improved Snow Depth Estimation (C-RISE) in the Indian Western Himalayas and Colorado Rocky Mountains by R. Chandra Prabha, Srinivasarao Tanniru, RAAJ Ramsankaran

“…Monitoring snow depth (SD) in mountainous regions is essential for water resource management, climate studies, and disaster predictions. Synthetic aperture radar (SAR)-based remote sensing, with its high spatial resolution and penetration capability, is more suited for such areas. …”
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Carbon balance dynamic evolution and simulation coupling economic development and ecological protection: a case study of Jiangxi Province at county scale from 2000–2030 by Yuliang Deng, Min Huang, Daohong Gong, Yong Ge, Hui Lin, Daoye Zhu, Yong Chen, Orhan Altan

“…This study introduces an analytical framework that couples economic development with ecological protection by using coupling coordination degree analysis, carbon balance zoning, and the Markov-PLUS model. Taking Jiangxi Province as a case study, we evaluate the spatio-temporal dynamics of carbon balance from 2000–2020 and predict future trends for 2030 under four potential development scenarios. …”
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Bridging Sensor Gaps via Attention-Gated Tuning for Hyperspectral Image Classification by Xizhe Xue, Haokui Zhang, Haizhao Jing, Lijie Tao, Zongwen Bai, Ying Li

“…Instead of inserting additional parameters inside the basic model, we train a lightweight auxiliary branch that takes intermediate features as input from the basic model and makes predictions. …”
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Ecological zone construction and multi-scenario simulation in Western China combining landscape ecological risk and ecosystem service value by Zihao Wang, Bing Wang, Yufei Zhang, Rula Sa, Qiuliang Zhang, Shuai Hao

“…By extending temporal scales using the PLUS model, it predicted the spatial patterns of ecological zones under four scenarios, achieving dynamic ecological zoning. …”
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Temporal generalization in evergreen leaf type classification using tailored Sentinel-2 composites by Peter Hofinger, Jan Dempewolf, Simon Ecke, Hans-Joachim Klemmt

“…Existing mapping approaches frequently suffer from spatial resolution limitations and temporal constraints. …”
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Planning for the future, algae bloom dynamics in water management and ecosystem restoration efforts by Paul Julian, William W. Walker, Donatto Surratt, Stephen E. Davis

“…The second model was a hierarchical model that used hydrodynamic and biogeochemical variables to predict chlorophyll-a concentrations across the lake. …”
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