New Trends in Image Classification and Pattern Recognition

Dear Colleagues,

In recent years, the fields of image classification and pattern recognition have witnessed rapid advancements driven by emerging technologies such as deep learning, edge computing and explainable artificial intelligence. The latest advancements in image classification and pattern recognition highlight emerging trends and innovations in these fields, which are crucial for various applications, including computer vision, artificial intelligence and data analysis. As traditional techniques evolve, new neural network architectures, such as deep convolutional neural networks (CNNs) and generative adversarial networks (GANs), are significantly improving the performance and efficiency of classification systems. The issue also examines the impact of integrating deep-learning and machine-learning methods with multi-channel image processing, big data analysis and practical applications in fields such as healthcare, environmental monitoring, autonomous vehicles, industrial automation, security and facial recognition. The goal is to showcase research that propose novel methodologies, innovative algorithms and cutting-edge applications, as well as studies that highlight the implications of these technologies in enhancing the accuracy and scalability of classification and pattern recognition systems.

Prof. Dr. Héctor Alonso Guerrero-Osuna
Dr. Luis Octavio Solís-Sánchez
Prof. Dr. Krzysztof Koszela
Guest Editors

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