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High accuracy positioning has become a key capability for fifth generation (5G) mobile networks and their future generations; however, the achievable performance is still severely limited by network time synchronization,...

Pixel-level segmentation is critical for remote sensing applications, yet traditional supervised methods suffer from high annotation costs. While foundational vision models like CLIP and the Segment Anything Model (SAM) ...

Manual cocoa bean inspection is subjective and prone to error, significantly impacting chocolate production. This study presents an automated, high-throughput cocoa bean grading system leveraging YOLOv10, YOLOv11, and Vi...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

Reliable prognostics in predictive maintenance requires not only accurate remaining useful life (RUL) estimation but also robustness under distribution shift and support for decision-making under uncertainty. However, mo...

An accurate intraoperative assessment of tissue perfusion in digestive surgery is critical to prevent complications such as anastomotic leakage, an event in which a surgical connection between organs fails to heal proper...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

Infrared thermal radiation signals are highly susceptible to environmental interference, leading to dynamic fluctuations. Consequently, weak targets are frequently submerged in heavy clutter backgrounds under extreme sce...

Dual-drive feed systems are widely adopted in high-end CNC machines because of their high precision, rigidity, and operational stability. Vibration suppression during machining is critical to maintaining feed accuracy an...

Zernike moments are well-suited for unmanned aerial vehicle scene matching because of their rotation invariance and robustness to noise. However, their high computational complexity poses challenges for meeting the real-...

Modern edge–cloud deployments integrate devices, edge servers, private networks, and cloud platforms into heterogeneous, multi-layer systems. Each layer exposes distinct metrics, measurement granularities, and tim...

Traffic congestion degrades urban mobility and economic productivity, yet existing sensor-based monitoring systems detect only where congestion occurs without distinguishing its underlying infrastructure causes. This pap...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

The Fast Steering Mirror (FSM) is a critical beam steering component in precision optical systems. However, its design often relies on repetitive finite element analysis (FEM) and experimentation due to the lack of unive...

This paper proposes a reinforcement learning framework for vision-based locomotion control of bipedal robots on complex, unstructured terrains, integrating privileged perception transfer, offline Transformer-based depth ...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

After an earthquake, numerous buildings are destroyed, and the frequency of structural collapses increases significantly in regions lacking comprehensive geophysical surveys. Furthermore, the number of deaths increases d...