Robust perception for aerial inspection: Adaptive and on-line techniques
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hdl:2117/178159
Document typePart of book or chapter of book
Defense date2019
PublisherSpringer
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Abstract
This chapter explains an adaptive on-line object detection and classification technique for robust perception due to varying scene conditions, for example partial cast shadows, change on the illumination conditions or changes in the angle of the object target view. This approach continuously updates the target model upon arrival of new data, being able to adapt to dynamic situations. The method uses an on-line learning technique that works on real-time and it is continuously updated in order to adapt to potential changes undergone by the target object. The method can run in real-time.
CitationVillamizar, M.; Sanfeliu, A. Robust perception for aerial inspection: Adaptive and on-line techniques. A: "Aerial robotic manipulation. Vol 129 of Springer tracts in advanced robotics". Berlín: Springer, 2019, p. 261-273.
ISBN978-3-030-12944-6
Publisher versionhttps://link.springer.com/chapter/10.1007%2F978-3-030-12945-3_19
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