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Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract.
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2017
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2014
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2014
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2015
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2015
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2015
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2016
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2016
Cited alongside, same era.
2017
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2017
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2017
Later among the works it cites.
2017
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2017
Later among the works it cites.
2017
Later among the works it cites.
M. Turan, Y. Almalioglu, H. Araujo, E. Konukoglu, and M. Sitti, “Deep endovo: A recurrent convolutional neural network (rcnn) based visual odometry approach for endoscopic capsule robots,” Neurocomputing , vol. 275, pp. 1861 – 1870, 2018. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S092523121731665X
2018
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M. Turan, Y. Y. Pilavci, I. Ganiyusufoglu, H. Araujo, E. Konukoglu, and M. Sitti, “Sparse-then-dense alignment-based 3d map reconstruction method for endoscopic capsule robots,” Machine Vision and Applications , vol. 29, no. 2, pp. 345–359, Feb 2018. [Online]. Available: https://doi.org/10.1007/s00138-017-0905-8
2018
Closest in time.