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Benjamin J. Meyer

2 accepted papers

2019

The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning

ICRA 2019poster

State-of-the-art deep neural network recognition systems are designed for a static and closed world. It is usually assumed that the distribution at test time will be the same as the distribution during training. As a result, classifiers are forced to categorise observations into one out of a set of…

Cited by 46Source ↗Scholar ↗
2017

Improved semantic segmentation for robotic applications with hierarchical conditional random fields

ICRA 2017poster

Conventional approaches to semantic segmentation are inappropriate for robotic applications, as they focus on pixel-level performance and give little significance to spurious object detections. This paper presents a region-based conditional random field model for semantic segmentation that focuses o…

Cited by 11Source ↗Scholar ↗