[robotics-worldwide] [journals] IJRR Special Issue on Deep Learning in Robotics: vol. 37, nos. 4-5, 2018

John Hollerbach jmh at cs.utah.edu
Mon Apr 30 13:51:49 PDT 2018

The International Journal of Robotics Research
<a href="https://urldefense.proofpoint.com/v2/url?u=http-3A__journals.sagepub.com_toc_ijra_37_4-2D5&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=TxErkogRQ8KW5kCmTY8lyvBbHI4GN4JN4-n77U9YnPc&s=P13dljWSnVlS3SSbnwZH110RqyyP85kuX6eQd-GUXvo&e=">
Special Issue on Deep Learning in Robotics</a>
Vol. 37, nos. 4-5, 2018


Special issue on deep learning in robotics
Niko Sünderhauf, Jürgen Leitner, Ben Upcroft, and Nicholas Roy


The limits and potentials of deep learning for robotics
Niko Sünderhauf, Oliver Brock, Walter Scheirer, Raia Hadsell, Dieter 
Fox, Jürgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, 
Michael Milford, and Peter Corke

Learning hand-eye coordination for robotic grasping with deep learning 
and large-scale data collection
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, and Deirdre 

RGB-D object detection and semantic segmentation for autonomous 
manipulation in clutter
Max Schwarz, Anton Milan, Arul Selvam Periyasamy, and Sven Behnke

Perceiving and reasoning about liquids using fully convolutional networks
Connor Schenck and Dieter Fox

Efficient and robust deep networks for semantic segmentation
Gabriel L Oliveira, Claas Bollen, Wolfram Burgard, and Thomas Brox

Deep tracking in the wild: End-to-end tracking using recurrent neural 
Julie Dequaire, Peter Ondrúška, Dushyant Rao, Dominic Wang, and Ingmar 

End-to-end, sequence-to-sequence probabilistic visual odometry through 
deep neural networks
Sen Wang, Ronald Clark, Hongkai Wen, and Niki Trigoni

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