14th IAPR Workshop on Pattern Recognition in Remote Sensing

In conjunction with 28th International Conference On Pattern Recognition (ICPR 2026). Please register on the ICPR website to participate.

Important Dates

August, 17-21, 2026 - International Conference On Pattern Recognition (ICPR 2026) in Lyon, France.

Aims and scope

As one of the flagship events of the International Association for Pattern Recognition, Pattern Recognition in Remote Sensing Workshop brings together researchers from both pattern recognition and remote sensing, with emphasis on the application of pattern recognition methods to remotely sensed data. The steady progress in the development of new remote sensing devices and remote sensing technology has led to ever-increasing data and new challenges. Thus, a need arises to apply the latest methods of machine learning and pattern recognition for automated analysis of this kind of data. This workshop will provide an ideal forum for spreading and exchanging the latest experiences of international researchers.

Topics

With the increase of availability of images and the importance of climate change, the Earth Observation and Remote Sensing fields have seen a growing interest. For instance, 50% of the EO satellites have been launched in the last 5 years. With this growing number of available data, a bottleneck in data representation and interpretation appeared. Many tasks of pattern recognition are therefore relevant to interpret remotely sensed data. During this day, we aim at covering the following topics:

Deep learning for Earth observation data
Foundation models for Earth observation data
Vision and language models for Earth observation
Semantic classification and parameter estimation from remote sensing data
Active, interactive and transfer learning
Multi-modal and multi-temporal analysis
Extraction, selection, learning, and reduction of features
Novel pattern recognition tasks in remote sensing applications
Explainable and interpretable machine learning
Hybrid models, combining physics and machine learning
Benchmark models and datasets

Organizers

IAPR Ethical Requirements for Authors

The IAPR requires that all authors wishing to present a paper declare that the paper is substantially original; that is, the manuscript as a whole, or for the most part, is novel, has not been published in (or even submitted to) any journals and has not been presented at any other conferences. If previous versions of the manuscript were published or presented, appropriate references must be given and substantial justification for presentation of the current version must be presented.

The IAPR strictly prohibits any plagiarism; that is, the work of others must not be “borrowed” and presented as the authors’ own work, regardless of the size of the borrowed portion.

The IAPR frowns upon “no-show behavior” at IAPR-related conferences and workshops, meaning that an author registers to make a presentation but does not show up for it. If such behavior is unavoidable due to urgent and unexpected personal matters, the author is strongly urged to notify the event organizer of the situation as soon as possible. If prior notification is impossible, the organizer should be advised after the fact of the reason for the author’s absence.

The IAPR retains the rights to eliminate any papers in violation of these Requirements and to take appropriate action against individuals repeatedly violating these Requirements and assumes no responsibility for any resulting loss of reputation or opportunity of such individuals or for any inconvenience related to the future work of such individuals.