Copy the page URI to the clipboard
Chiatti, Agnese; Motta, Enrico and Daga, Enrico
(2022).
URL: https://www.aaai-make.info/
Abstract
To effectively assist us with our daily tasks, service robots need object recognition methods that perform robustly in dynamic environments. Our prior work has shown that augmenting Deep Learning (DL) methods with knowledge-based reasoning can drastically improve the reliability of object recognition systems. This paper proposes a novel method to equip DL-based object recognition with the ability to reason on the typical size and spatial relations of objects. Experiments in a real-world robotic scenario show that the proposed hybrid architecture significantly outperforms DL-only solutions.
Viewing alternatives
Download history
Item Actions
Export
About
- Item ORO ID
- 81576
- Item Type
- Conference or Workshop Item
- Keywords
- commonsense reasoning; visual intelligence; hybrid intelligence; service robotics
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Intelligent Systems and Data Science
- Copyright Holders
- © 2022 Agnese Chiatti, © 2022 Enrico Motta, © 2022 Enrico Daga
- Depositing User
- Agnese Chiatti