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Electronic Supplementary Material Supplementary material is available for this article at 10.1007/s11432-015-5347-1 and is accessible for authorized users.
Deep learning and Feature learning emerged new field in machine learning and beat many, state of the arts results in diverse areas. Well established feature learning Sparse-Auto encoder was chosen in our work and tunes their different critical parameters. We have shown that tweaking right parameter can improved results and good features can be obtained. Different Whitening preprocessing techniques...
Simultaneous Localization and Mapping, SLAM, is a prime requirement for autonomous navigation and it is an integral part of a modern robot. An incremental appearance only SLAM based on non-quantized local features drastically suffers from large number of landmarks detected in the captured imagery. In order to decrease the number of landmarks, we propose a visual saliency model that is used as first...
Infrared-landmark based vision navigation system is proposed to reliably guide drivers from starting point to goal following a feasible shortest path in a known indoor or outdoor environment no matter whether it is day or night. What's more, this system is capable of warning drivers about the dangerous zones “like no right turn, no U-turn, damaged road ahead etc” conditions when no visible light is...
Simultaneous Localization and Mapping, SLAM, is an important topic in the field of robotics and autonomous navigation. The metric SLAM suffers from sensor inaccuracies and thus cannot be used for long-term navigation. In such case, Visual SLAM or a Hybrid SLAM based on both metric and visual approach is a good alternative. In this paper, in order to speed up a Visual SLAM, we propose a novel concept...
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