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The International journal of robotics research, ISSN 0278-3649, 4/2018, Volume 37, Issue 4-5, pp. 405 - 420
The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and... 
robotic vision | deep learning | machine learning | Robotics | NEURAL-NETWORKS | OBJECT | SIMULATION | Computer vision | Computer simulation | Machine learning
Journal Article
Autonomous Robots, ISSN 0929-5593, 10/2015, Volume 39, Issue 3, pp. 363 - 387
Journal Article
Journal of Field Robotics, ISSN 1556-4959, 01/2017, Volume 34, Issue 1, pp. 53 - 73
This paper addresses the problem of detecting people and vehicles on a surface mine by presenting an architecture that combines the complementary strengths of... 
ROBOTICS | Mineral industry | Mining industry | Strip mining | Images | Feature extraction | Recall | Data mining | Proposals | Object recognition | Mines | Heavy vehicles
Journal Article
The International journal of robotics research, ISSN 0278-3649, 4/2018, Volume 37, Issue 4-5, pp. 403 - 404
Journal Article
Journal of field robotics, ISSN 1556-4959, 2016, Volume 33, Issue 8, pp. 1107 - 1130
Journal Article
Journal of field robotics, ISSN 1556-4959, 2017, Volume 34, Issue 6, pp. 1039 - 1060
Journal Article
Springer Tracts in Advanced Robotics, ISSN 1610-7438, 2016, Volume 113, pp. 501 - 514
Conference Proceeding
Remote sensing (Basel, Switzerland), ISSN 2072-4292, 2016, Volume 8, Issue 2, p. 113
Journal Article
The International Journal of Robotics Research, ISSN 0278-3649, 4/2016, Volume 35, Issue 4, pp. 381 - 403
Visual Odometry is a key technology for robust and accurate navigation of unmanned aerial vehicles in a number of low altitude applications (<120 m),... 
unmanned aerial vehicles | visual odometry | Stereo vision | POSE ESTIMATION | ROBOTICS | VISION | NAVIGATION | GPS | Usage | Analysis | Drone aircraft | Odometers | Research | Automobiles | Algorithms | Navigation | Cameras | Unmanned aerial vehicles | Detection | Visual | Global Positioning System | Altitude
Journal Article
Journal Article
Journal of Field Robotics, ISSN 1556-4959, 12/2015, Volume 32, Issue 8, pp. 1114 - 1140
A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land... 
ROBOTICS | GUIDANCE | Aircraft accidents & safety | Automation | Unmanned aerial vehicles
Journal Article
IET Computer Vision, ISSN 1751-9632, 2/2014, Volume 8, Issue 1, pp. 45 - 53
... 1751-9632 Automatic object segmentation of unstructured scenes using colour and depth maps Hu He, Ben Upcroft School of Electrical Engineering and Computer Science... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Journal of Spacecraft and Rockets, ISSN 0022-4650, 01/2014, Volume 51, Issue 1, pp. 31 - 38
... Tracking Timothy J. McIntyre, Razmi Khan, Troy N. Eichmann, and Ben Upcroft University of Queensland, Brisbane, Queensland 4072, Australiaand David Buttsworth... 
ENGINEERING, AEROSPACE | Near infrared radiation | Japanese spacecraft | Infrared spectroscopy | Spectral emittance | Reentry | Spectrum analysis | Infrared tracking | Nitrogen atoms | Black body radiation | Line spectra | Gas temperature | Earth atmosphere | Spectrographs | Tracking | Spacecraft | Vehicles
Journal Article
2016 IEEE International Conference on Image Processing (ICIP), ISSN 1522-4880, 09/2016, Volume 2016-, pp. 3464 - 3468
This paper explores a pragmatic approach to multiple object tracking where the main focus is to associate objects efficiently for online and realtime... 
Visualization | Target tracking | Data Association | Detectors | Benchmark testing | Complexity theory | Multiple Object Tracking | Kalman filters | Computer Vision | Detection | Computer Science - Computer Vision and Pattern Recognition
Conference Proceeding
Journal of field robotics, ISSN 1556-4959, 2017, Volume 34, Issue 6, pp. 1123 - 1139
Journal Article
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), ISSN 2153-0858, 09/2015, Volume 2015-, pp. 4297 - 4304
After the incredible success of deep learning in the computer vision domain, there has been much interest in applying Convolutional Network (ConvNet) features... 
Visualization | Computer vision | Feature extraction | Robustness | Real-time systems | Semantics | Networks | Navigation | Real time | Robotics | Recognition | Robots
Conference Proceeding