Today partly, extraction, recognition and analysis of visual patterns have been accomplished using machine learning, deep learning, intelligent systems, software computing, information retrieval and statistical analysis in multiple real-life contexts and scenarios. The 2nd International Workshop on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2020) is intended to be an international forum whose main goal is presenting the advancement of the state-of-the-art, innovative research, ongoing work, academic and project reports in statistics and data mining, as well as applied mathematics, knowledge representation, intelligent systems, information retrieval and software engineering, for visual pattern extraction, analysis and recognition aiming to preserve the cultural heritage. The event was organised as an international research forum by the University of Calabria and the Uppsala University.

VIPERC 2020: Visual pattern extraction and recognition for cultural heritage understanding

Amelio A.;
2020-01-01

Abstract

Today partly, extraction, recognition and analysis of visual patterns have been accomplished using machine learning, deep learning, intelligent systems, software computing, information retrieval and statistical analysis in multiple real-life contexts and scenarios. The 2nd International Workshop on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2020) is intended to be an international forum whose main goal is presenting the advancement of the state-of-the-art, innovative research, ongoing work, academic and project reports in statistics and data mining, as well as applied mathematics, knowledge representation, intelligent systems, information retrieval and software engineering, for visual pattern extraction, analysis and recognition aiming to preserve the cultural heritage. The event was organised as an international research forum by the University of Calabria and the Uppsala University.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/770144
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