Enhancing Deep Learning Sustainability by Synchronized Multi Augmentation with Rotations and Multi-Backbone Architectures by Nikita Gordienko, Yuri Gordienko, Sergii Stirenko

“…Deep learning applications for Edge Intelligence (EI) face challenges in achieving high model performance while maintaining computational efficiency, particularly under varying image orientations and perspectives. …”
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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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Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States by Meredith M. Brehob, Michael J. Pennino, Amalia M. Handler, Jana E. Compton, Sylvia S. Lee, Robert D. Sabo

“…We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. …”
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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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Interface Thermal Conductance of Nonequilibrium Thermal Transport across Nanoscale Metal Multilayers by Donghao Li, Zhongyin Zhang, Ziyang Wang, Gen Li, Jing Zhou, Jie Zhu, Dawei Tang

“…These experiment results revealed that nonequilibrium ITC at the Au/Cr interface closely matched the predicted value of 6 GW m−2 K−1 by the electronic diffuse mismatch model, which captures ultrafast thermal behavior within the first few picoseconds following femtosecond laser heating. …”
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HO 2 Generation Above Sprite‐Producing Thunderstorms Derived from Low‐Noise SMILES Observation Spectra by T. Yamada, T. O. Sato, T. Adachi, H. Winkler, K. Kuribayashi, R. Larsson, N. Yoshida, Y. Takahashi, M. Sato, A. B. Chen, R. R. Hsu, Y. Nakano, T. Fujinawa, S. Nara, Y. Uchiyama, Y. Kasai

“…A total of three areas was identified with enhanced HO 2 levels of approximately 10 25 molecules. A chemical sprite model indicates an increase in HO 2 in the considered altitude region; however, the predicted production due to a single sprite event is smaller than the observed enhancement. …”
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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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Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

“…This study highlights the robustness of support vector regression and accentuates the impact of climatic and environmental conditions on model performance, ultimately contributing to more precise predictions of latent heat flux.…”
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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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Fast and Accurate Plane Wave and Color Doppler Imaging with the FOCUS Software Package by Jacob S. Honer, Robert J. McGough

“…Simulation results demonstrate rapid convergence and lower error rates compared to conventional spatial impulse response methods and Field II, resulting in substantial reductions in computation time. …”
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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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An MCMC Approach to Bayesian Image Analysis in Fourier Space by Konstantinos Bakas, John Kornak, Hernando Ombao

“…Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection. …”
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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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SkelETT—Skeleton-to-Emotion Transfer Transformer by Pedro Victor Vieira Paiva, Josue Junior Guimaraes Ramos, Marina Gavrilova, Marco Antonio Garcia de Carvalho

“…By exposing the model to an extensive corpus of unlabeled human skeleton data, we can effectively learn to represent complex spatial and temporal dependencies inherent in body movements. …”
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Monitoring sub-arctic wetland vegetation using nested scales of spectrometry to inform multiple endmember spectral unmixing of Sentinel-2A imagery by Heidi Cunnick, Joan M Ramage, Dawn Magness, Stephen C Peters

“…We develop a bottom–up reference library for unmixing based on nested scales of data beginning with the highest resolution of a ground collected handheld spectral measurements, progressing to 1 m ^2 resolution using fused hyperspectral-LiDAR data, and then subsequently map predictively at the spatial resolution of the 10 m ^2 multi-spectral imagery of the European Space Agency’s Sentinel-2A. …”
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Retrospective evaluation of Facial nerve monitoring to prevent nerve damage during robotic drilling in the largest series of patients undergoing the HEARO-procedure. by Jaouad Abari, Marco Matulic, Pablo Galeazzi, Masoud Zoka Assadi, Paul Van de Heyning, Vedat Topsakal

“…Linear regression was used to determine if the minimum stimulation thresholds (FNM) could significantly predict the intra-operative distance (CBCT) between the drilled trajectory and the facial nerve. …”
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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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Shafranov-shift destabilization of ballooning-type micro-instabilities by X. Jian, V. Chan, Z. Qiu, S. Ding, C. Holland, E. Bass, A. Garofalo, X. Liu

“…However, this improvement is limited to a very narrow spatial region while ${\omega _{\text{d}}}$ is increased over the remaining poloidal space. …”
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