Abstract: Remote sensing images are usually characterized by complex backgrounds, scale and orientation variations, and large intraclass variance. General semantic segmentation methods usually fail to ...

Abstract: Current orthopedic surgical robots are widely used in pedicle screw implantation tasks due to their precise positioning capabilities. However, the surgical operation processes, including ...

Abstract: Next Point-of-interest recommendation involves modeling user interactions with Point-of-interests (PoIs) to analyze user behavior patterns and suggest future scenarios. Data sparsity ...

Abstract: As a cornerstone in the Evolutionary Computation (EC) domain, Differential Evolution (DE) is known for its simplicity and effectiveness in handling challenging black-box optimization ...

Abstract: This brief presents a resolution-reconfigurable successive-approximation-register (SAR) analog-to-digital converter (ADC). The reconfigurable capacitor digital-to-analog converter (CDAC) is ...

Abstract: To improve the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor (PMSM) system, an adaptive super-twisting nonsingular terminal sliding mode ...

Abstract: Light detection and ranging (LiDAR) point cloud compression (LPCC) plays an important role in managing the storage, transmission, and perception of the rapidly expanding volume of LiDAR ...

Abstract: Change detection aims to reveal the changes of specific regions or objects in a time series. Object-level change detection methods are more suitable for existing needs because they can ...

Abstract: With the continuous development of the power system, in the face of the frequency deviation caused by the randomness and volatility of renewable energy sources such as photovoltaic and wind ...

Abstract: Over the past decades, the number of submitted articles that use numerical approaches for SPICE models or for characterization (extraction) of parameters of existing SPICE models has grown ...

Abstract: This paper introduces a novel optimized hybrid model combining Long Short-Term Memory (LSTM) and Transformer deep learning architectures designed for power load forecasting. It leverages the ...

Abstract: This study presents a brain-computer interface (BCI) approach that uses optically pumped magnetometers (OPMs)-based magnetoencephalography (MEG) associated with motor imagery (MI) for the ...