The IEEE 16th International Conference on Pattern Recognition Systems (ICPRS-27) is an annual international event that follows ICPRS-25, ICPRS-24, ICPRS-23, ICPRS-22, ICPRS-21, ICPRS-19, ICPRS-18, ICPRS-17 and ICPRS-16, a continuation of the successful Chilean Conference on Pattern Recognition that reached its 6th edition in 2014. In 2027 it is organised by the Université de Bordeaux (France) and the Chilean Association for Pattern Recognition (ACHiRP, a member of the IAPR), and as previous years it is endorsed by the IAPR and the IEEE Chile/UK/France Sections. Papers deemed to be of the required standard AND presented at the conference, are planned to be published by the IEEE and indexed in IEEE Xplore. Please note that the publishers might reject papers which are too similar to previous publications, even if the work is presented at the conference. All paper submissions need to be submitted via Conftool to be peer-reviewed (double-blind) by an international panel of experts. For more information, please see https://www.icprs.org. There will be a good set of keynote talks. ICPRS 2027 is planned to be a 100% in person. There is also a special “Student Paper” category for papers whose main author is a registered student at the time of submission.

Prospective authors are invited to submit papers describing novel and previously unpublished results on topics including, but not limited to:
• Artificial Intelligence Techniques in Pattern Recognition
• Bioinformatics Clustering
• Biometrics (including face recognition)
• Computer Vision
• Data Mining and Big Data
• Dataset: a new public dataset and baseline
• Deep Learning and Neural Networks for Pattern Recognition
• Document Processing and Recognition
• Fuzzy and Hybrid Techniques in PR
• High Performance Computing for Pattern Recognition
• Image Processing and Analysis
• Kernel Machines
• Mathematical Morphology
• Mathematical Theory of Pattern Recognition
• Medical Image Processing and Analysis
• Natural Language Processing and Recognition
• Object Detection, Tracking and Recognition
• Pattern Recognition Principles
• Pattern Recognition for optimization
• Real Systems, Applications and Case Studies of Pattern Recognition (e.g. health, environment, weather prediction, natural disasters, transportation, etc.)
• Robotics
• Remote Sensing
• Shape and Texture Analysis
• Signal Processing and Analysis
• Social Media and HCI
• Signal Processing and Analysis
• Statistical Pattern Recognition
• Syntactical and Structural Pattern Recognition
• Time series prediction
• Voice and Speech Recognition