Review
Version 1
Preserved in Portico This version is not peer-reviewed
Zero Shot Learning Recent Advances in Robotics
Version 1
: Received: 18 June 2023 / Approved: 19 June 2023 / Online: 20 June 2023 (04:40:47 CEST)
How to cite: Singh, S. Zero Shot Learning Recent Advances in Robotics. Preprints 2023, 2023061353. https://doi.org/10.20944/preprints202306.1353.v1 Singh, S. Zero Shot Learning Recent Advances in Robotics. Preprints 2023, 2023061353. https://doi.org/10.20944/preprints202306.1353.v1
Abstract
Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.
Keywords
zero-shot learning; robotics
Subject
Engineering, Electrical and Electronic Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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