Advanced image processing (AIP) and computer vision (CV) remain dynamic and rapidly evolving research areas that drive innovation across a wide range of real-world applications. AI has become a fundamental enabler of AIP and CV, enhancing their capabilities and expanding their impact in multiple domains. While current AI-based algorithms have achieved impressive results through data-driven approaches, many challenges persist, particularly when dealing with limited or low-quality data. These limitations highlight the need for novel methods that are capable of improving accuracy, robustness, and adaptability in complex environments.

This Reprint brings together original research articles, comprehensive reviews, and in-depth technical studies focused on the development and application of innovative AI-based algorithms for AIP and CV. It emphasizes emerging approaches that address data scarcity, optimize performance in critical settings, and align with human-centric principles, including ethical and fair AI. Although special attention is given to medical and healthcare applications, the Reprint also reflects the broader relevance of these technologies across agriculture, environmental monitoring, and other applied fields.

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