Derin Ögrenme Tabanli Otonom Yön Belirleme

Hulya Yalcin, M. Husrev Cilasun

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

Özet

Outdoor mapping and localization based on appearance is especially challenging since usually separate processes of mapping and localization are required at different times of day. The problem is harder in the outdoors where continuous change in sun angle can drastically affect the appearance of a scene. In this work, we propose a method for instantaneous visual direction determination for the autonomous mobile platforms assuming the mobile platform travels along a routine route. We propose a deep convolutional neural network based algorithm for classification of instantaneous images of the path to be followed. The model is tested on SeqSlam dataset and a success performance of %78.5 is achieved. Hidden layer weights are analyzed to ensure that the learning is actually achieved. Experimental results suggest that deep neural networks yield high recognition rates of images to be used for autonomous movement. Approach will be tested on a novel dataset and its performance will be realized in realtime as future work.

Tercüme edilen katkı başlığıDeep learning based autonomous direction estimation
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar1645-1648
Sayfa sayısı4
ISBN (Elektronik)9781509016792
DOI'lar
Yayın durumuYayınlandı - 20 Haz 2016
Etkinlik24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey
Süre: 16 May 201619 May 2016

Yayın serisi

Adı2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

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???event.eventtypes.event.conference???24th Signal Processing and Communication Application Conference, SIU 2016
Ülke/BölgeTurkey
ŞehirZonguldak
Periyot16/05/1619/05/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

Keywords

  • appearance based localization and mapping
  • autonomous direction determination
  • deep learning
  • deep neural networks

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