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As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Reliable trajectory similarity estimation underpins applications such as map matching, mobility anomaly detection, and travel behavior analysis. However, traditional distance-based methods are computationally expensive a...

To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

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...

Goal: Analysis of the glottal area during vocal fold vibration has gained increasing attention. However, traditional analysis requires manual, frame-by-frame glottal area annotation to compute the glottal area waveform, ...

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-...

The detection of transmission towers in remote sensing images presents significant challenges due to insufficient feature representation and significant object size variations, particularly at low spatial resolutions whe...

Unmanned aerial vehicle (UAV) aerial photography technology is crucial in various fields, including daily life, production, and security. However, it faces challenges in small object detection, such as extremely small ob...

Skin lesion segmentation poses a challenging problem in medical image analysis, with segmentation performance being highly sensitive to blurred boundaries, noise interference, and morphological diversity. To address thes...

Multimodal remote sensing image registration is a fundamental step for multisource data fusion and geospatial analysis. However, nonlinear radiometric, textural, and geometric discrepancies across modalities challenge in...

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...

Intelligent tire systems (ITS) enable direct sensing of tire and road interaction using sensors mounted inside the tire, providing information that is difficult to obtain from conventional vehicle-mounted sensors. Howeve...

With the rapid advancement of remote sensing technology, target detection in remote sensing imagery plays a crucial role in military reconnaissance, urban planning, and other fields. However, there are problems such as l...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

To address issues such as missed detections and false positives in safety equipment wear detection tasks caused by complex backgrounds, severe occlusions, and small target sizes, as well as frequent ID switching and low ...

High-quality lunar imaging is essential to terrain modeling, resource assessment, and landing navigation. However, due to the limited depth-of-field of lunar probe cameras, a single image cannot simultaneously capture cl...

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...

Buildings serve as a key indicator of human land use, and building change detection plays a crucial role in urban growth and shrinkage monitoring, land use planning, and urban development assessment and management. Curre...

Sleep plays an important role in physical health, cognition, and emotional well-being. Since sleep disorders can affect all these aspects, accurately detecting sleep stages is key to proper diagnosis and monitoring. Auto...

The inherent non-stationarity, weak periodicity, and abrupt transient mutations of wind turbine gearbox vibration signals present substantial challenges to traditional diagnostic frameworks. To improve diagnostic accurac...

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...