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Special session Multiscale à ICPRAI 2022

2 Novembre 2021

Catégorie : Conférence internationale

Dear colleagues,

In the context of the 3rd International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI'22), held in Paris (1-3 June 2022), we organize a Special session named Multiscale focusing on Analysis and learning of multi-variate, multi-temporal, multi-resolution and multi-source remote sensing data (hereafter denoted as multi* remote sensing data). This special session will be an opportunity to give an overview of recent progress of PRAI research studies, in which new methodological, computational and practical achievements dedicated to multivariate remote sensing data will be presented. It also will be a renewed opportunity to gather PRAI and domain-experts researchers, in order to exchange, debate and draw short and long term research objectives around the exploitation, analysis and processing of multimodal remote sensing data coming from heterogeneous sensors. The aim is to stimulate concrete discussions to pave the way to new frameworks especially tailored in the domain.

Special session website:

Key dates:

  • Paper submission deadline : December 15th, 2021
  • Author notification : March 8th, 2022
  • Camera ready deadline : March 22th, 2022
  • Conference : June 1rst-3rd, 2022


We welcome contributions of both technical and perspective papers from a wide range of topics, including but not limited to the following topics of interest:

  • Artificial intelligence applied to multi* remote sensing data
  • Recognition of patterns, objects and targets from multi* remote sensing data
  • 2D/3D remote sensing data analysis and processing
  • Multi* remote sensing image classification, retrieval and semantic segmentation
  • Machine learning, deep learning approaches to deal with multi* remote sensing data
  • Analysis of multi-resolution remote sensing images
  • Fusion of multi-source remote sensing data
  • Multi-temporal remote sensing data analysis and classification
  • Transfer Learning and domain adaptation for multi* remote sensing data
  • Feature extraction and feature selection for multi* remote sensing data
  • Multi-task learning from multi* remote sensing data


Submission website: Submissions can be submitted in easychair website ( and select the track SS - Analysis and learning of multi-variate, multi-temporal, multi-resolution and multi-source remote sensing data”.


Accepted papers will be presented at the conference in a special session and will be published by Springer in the Lecture Notes in Computer Science. Articles should be prepared according to the LNCS author guidelines and templates and they should be at most twelve pages long. Submissions will be peer-reviewed by at least 3 reviewers and assessed based on their novelty, clarity significance, and relevance regarding the special session topics. Submissions that are already accepted or under review for another venue are not accepted.

Kindky regard,

The SS co-chairs,

Laetitia Chapel, Minh-Tan Pham, Erchan Aptoula, and Sébastien Lefèvre