Fusion and binarization of CNN features for robust topological localization across seasons

By Roberto Arroyo, Pablo Fernández Alcantarilla, Luis Miguel Bergasa, Eduardo Romera. 2016

97 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Lei Tai

In Computer Vision and Pattern Recognition

1. Lei Tai
2. Ming Liu

Citations in the corpus

• A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation (2016, neutral): “ecognition in robotics was proved as well. It also proposed that mid and high-level features from the CNN models were more robust for the changes of appearance and viewpoint. Naseer et al. (2015) and Arroyo et al. (2016) showed that features extracted by convolutional models for place recognition we”
• Deep-learning in Mobile Robotics - from Perception to Control Systems: A Survey on Why and Why not (2016, background): “For reinforcement learning, it is more like an optimization problem.”