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Driven by satellite remote sensing observations, deep learning models provide a promising solution for the rapid estimation of subsurface thermohaline structures. By learning from large-scale paired surface–subsur...

Farmer credit default identification in the context of inclusive finance is significantly hindered by sample scarcity, heterogeneous data sources, and the underutilization of “soft information” embedded in ...

Artistic style transfer has long been possible with the advancements of convolution- and transformer-based neural networks. Most algorithms apply the artistic style transfer to the whole image, but individual users may o...

Measurements from global navigation satellite system reflectometry (GNSS-R) have proven effective for applications in sea surface height (SSH). Deep learning-based methods for spaceborne GNSS-R SSH retrieval can effectiv...

Time-series forecasting is fundamental to decision-making across numerous domains; however, systematic temporal delays in predictions remain a largely overlooked or unrecognised phenomenon. This phenomenon occurs when fo...

With advances in aerospace technology, high-resolution optical imagery from satellites, such as China’s Gaofen series, is vital for climate monitoring and agriculture. However, cloud cover significantly impedes th...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Digital health increasingly relies on artificial intelligence for clinical decision-making, patient management, and distributed learning, yet two persistent challenges remain: the computational complexity of optimization...

Robot Operating System (ROS) is a middleware widely used in robotics development. ROS simplifies communication between nodes within a network so that robot developers are able to simply develop robot applications. Howeve...

Camera rigs for Advanced Driver Assistance Systems (ADAS) are subject to design choices of each vehicle variant; therefore, ADAS algorithms should be rig-invariant or tunable with limited additional data. Recently, the A...

Question-answering (QA) has been a crucial NLP (Natural Language Processing) task for a long time. As an umbrella term, QA has multiple sub-tasks under its hood. Question classification (QC) is one of the most important ...

Time series analysis is essential for finance, transportation, energy, healthcare, and climate research. While time-frequency domain representation underpins effective time series modeling, its holistic utilization and i...

Convolutional neural networks (CNNs) and visual Transformers have become the dominant approaches for hyperspectral image (HSI) classification due to their powerful feature representation capabilities. However, CNNs are l...