Document Analysis Research in the Year 2021

The original publication is available at www.springerlink.comInternational audienceDespite tremendous advances in computer software and hardware, certain key aspects of experimental research in document analysis, and pattern recognition in general, have not changed much over the past 50 years. This paper describes a vision of the future where community-created and managed resources make possible fundamental changes in the way science is conducted in such fields. We also discuss current developments that are helping to lead us in this direction

Interpretation, Evaluation and the Semantic Gap ... What if we Were on a Side-Track?

International audienceA significant amount of research in Document Image Analysis, and Machine Perception in general, relies on the extraction and analysis of signal cues with the goal of interpreting them into higher level information. This paper gives an overview on how this interpretation process is usually considered, and how the research communities proceed in evaluating existing approaches and methods developed for realizing these processes. Evaluation being an essential part to measuring the quality of research and assessing the progress of the state-of-the art, our work aims at showing that classical evaluation methods are not necessarily well suited for interpretation problems, or, at least, that they introduce a strong bias, not necessarily visible at first sight, and that new ways of comparing methods and measuring performance are necessary. It also shows that the infamous {\em Semantic Gap} seems to be an inherent and unavoidable part of the general interpretation process, especially when considered within the framework of traditional evaluation. The use of Formal Concept Analysis is put forward to leverage these limitations into a new tool to the analysis and comparison of interpretation contexts

The Latin Supine and the French Infinitive

status: publishe