Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

Neural architecture search (NAS) has attracted increasing attention. In recent years,
individual search methods have been replaced by weight-sharing search methods for higher …

Low-light image enhancement plays very important roles in low-level vision areas. Recent
works have built a great deal of deep learning models to address this task. However, these …

In the past decade, advances in deep learning have resulted in breakthroughs in a variety of
areas, including computer vision, natural language understanding, speech recognition, and …

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …

Multi-scale neural networks have shown effectiveness in image restoration tasks, which are
usually designed and integrated in a handcrafted manner. Different from the existing labor …

Nowadays, driven by the high demand for autonomous driving and surveillance, infrared
and visible image fusion (IVIF) has attracted significant attention from both the industry and …

Image stitching is a fundamental task that requires multiple images from different viewpoints
to generate a wide field-of-viewing~(FOV) scene. Previous methods are developed on RGB …

Multi-scale and multi-patch deep models have been shown effective in removing blurs of
dynamic scenes. However, these methods still have one major obstacle: manually designing …

Multi-modality image fusion refers to generating a complementary image that integrates
typical characteristics from source images. In recent years, we have witnessed the …