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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...

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...

Remote sensing enables urban planners to gain macroscopic insights into urban structures and issues. Pan-sharpening plays a key role by merging multispectral and panchromatic images, combining high spatial resolution wit...

Fine-grained remote sensing ship detection plays an important role in maritime traffic management and the security guarantee system. Despite considerable research advances have been achieved via elaborately designed deep...

This review addresses the urgent need for scalable, accurate, and reproducible remote sensing solutions following the February 2023 Türkiye earthquakes. It synthesizes the contributions of five peer-reviewed studi...

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...

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...

Infrared dim and small target detection is crucial in fields, such as military reconnaissance and remote sensing. However, due to the extremely small target size, lack of texture, and low signal-to-noise ratio, the direc...

Weakly supervised semantic segmentation (WSSS), particularly using image-level labels, has emerged as a pivotal solution to alleviate the burden of costly and labor-intensive pixel-level annotations typically required fo...

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...

Hyperspectral single image super-resolution (HS-SISR) aims to enhance the spatial resolution of hyperspectral images to fully exploit their spectral information. While considerable progress has been made in this field, m...

The design of a bistatic inverse synthetic aperture radar (ISAR) images simulator is described, as a response to the need of databases with classification purposes in bistatic radar scenarios characterized by numerous de...