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Deep learning has allowed a paradigm shift in pattern recognition, from usinghand-crafted features together with statistical classifiers to usinggeneral-purpose learning procedures for learning data-driven representations,features, and classifiers together. The application of this new paradigm hasbeen particularly successful in computer vision, in which the development ofdeep learning methods for vision applications has become a hot research topic.Given that deep learning has already attracted the attention of the robotvision community, the main purpose of this survey is to address the use of deeplearning in robot vision. To achieve this, a comprehensive overview of deeplearning and its usage in computer vision is given, that includes a descriptionof the most frequently used neural models and their main application areas.Then, the standard methodology and tools used for designing deep-learning basedvision systems are presented. Afterwards, a review of the principal work usingdeep learning in robot vision is presented, as well as current and futuretrends related to the use of deep learning in robotics. This survey is intendedto be a guide for the developers of robot vision systems.

A Survey on Deep Learning Methods for Robot Vision