Pattern Recognition and Image Processing: Latest Advances and Prospects

Dear Colleagues,

Pattern recognition and image processing are areas of significant interest whose extensive applicability ranges from areas such as medicine, biology, industrial automation, security, and remote sensing. While image processing focuses on analyzing and extracting information from images, pattern recognition aims to analyze data in different formats such as images, texts and audio to automatically detect patterns and regularities existing in the data. The technological evolution of computer systems and the search for solutions with increasingly higher levels of performance, both in terms of precision and reliability, as well as in terms of processing speed, has led to a major evolution in pattern recognition and image processing techniques. The utilization of non-learning-based methods has given way to machine learning techniques, where deep learning methods have been the focus in recent decades. Regarding the use of neural networks, there is a tendency towards proposals based on the modification of families of already established networks, the combination of different networks, the fusion of the results of networks with independent operation, the combination of neural networks with other machine learning methods, or even the application of learning transfer models.

This Special Issue intends to compile high-quality theoretical and applied research contributions in the areas of pattern recognition and image processing, with application in different domains. Potential topics include, but are not limited to, image analysis, image enhancement and reconstruction, image segmentation, classification and retrieval, image coding and compression, image interpretation and registration, motion detection and estimation, pattern recognition, and other related areas.

Dr. Sandra V.B. Jardim
Dr. Rolando Miragaia
Dr. José Carlos Bregieiro Ribeiro
Guest Editors

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• image processing
• pattern recognition and analysis
• visualization
• image coding and compression
• image retrieval
• image segmentation and classification
• computational imaging
• motion detection