A Review on Intelligent Object Perception Methods Combining Knowledge-based Reasoning and Machine Learning

Autor:	Gouidis, Filippos, Vassiliades, Alexandros, Patkos, Theodore, Argyros, Antonis, Bassiliades, Nick, Plexousakis, Dimitris
Rok vydání:	2019
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Artificial Intelligence Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Object perception is a fundamental sub-field of Computer Vision, covering a multitude of individual areas and having contributed high-impact results. While Machine Learning has been traditionally applied to address related problems, recent works also seek ways to integrate knowledge engineering in order to expand the level of intelligence of the visual interpretation of objects, their properties and their relations with their environment. In this paper, we attempt a systematic investigation of how knowledge-based methods contribute to diverse object perception tasks. We review the latest achievements and identify prominent research directions.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1912.11861 Zobrazit plný text záznamu View this record from Arxiv