Domain Adaptation with L2 constraints for classifying images from different endoscope systems

8 Nov 2016Toru TamakiShoji SonoyamaTakio KuritaTsubasa HirakawaBisser RaytchevKazufumi KanedaTetsushi KoideShigeto YoshidaHiroshi MienoShinji TanakaKazuaki Chayama

This paper proposes a method for domain adaptation that extends the maximum margin domain transfer (MMDT) proposed by Hoffman et al., by introducing L2 distance constraints between samples of different domains; thus, our method is denoted as MMDTL2. Motivated by the differences between the images taken by narrow band imaging (NBI) endoscopic devices, we utilize different NBI devices as different domains and estimate the transformations between samples of different domains, i.e., image samples taken by different NBI endoscope systems... (read more)

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