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Marianne Bakken

2 accepted papers

2021

Robot-supervised Learning of Crop Row Segmentation

ICRA 2021poster

We propose an approach for robot-supervised learning that automates label generation for semantic segmentation with Convolutional Neural Networks (CNNs) for crop row detection in a field. Using a training robot equipped with RTK GNSS and RGB camera, we train a neural network that can later be used f…

Cited by 11SourceScholar
2020

Principal Feature Visualisation in Convolutional Neural Networks

ECCV 2020poster

We introduce a new visualisation technique for CNNs called Principal Feature Visualisation (PFV). It uses a single forward pass of the original network to map principal features from the final convolutional layer to the original image space as RGB channels. By working on a batch of images we can ext…