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Published in 2017 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-017-1651-0
Abstract: PurposeThis study investigates an efficient (nearly real-time) two-stage spine labeling algorithm that removes the need for an external training while being applicable to different types of MRI data and acquisition protocols.MethodsBased solely on the image…
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Keywords:
distribution matching;
spine labeling;
external training;
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Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.05.098
Abstract: Abstract When the distributions between the source (training) and target (test) datasets are different, the performance of classical statistical learning methods degrades significantly. Domain adaptation (DA) aims at correcting this distribution mismatch and narrowing down…
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Keywords:
matching embedding;
joint distribution;
domain adaptation;
distribution matching ... See more keywords
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Published in 2019 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2018.2881091
Abstract: Distribution matching is a fixed-length invertible mapping from a uniformly distributed bit sequence to shaped amplitudes and plays an important role in the probabilistic amplitude shaping framework. With conventional constant-composition distribution matching (CCDM), all output…
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Keywords:
partition distribution;
multiset partition;
distribution;
composition ... See more keywords
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Published in 2020 at "Optics express"
DOI: 10.1364/oe.413024
Abstract: This paper proposes a probabilistic shaping orthogonal frequency division multiplexing passive optical network (PS-OFDM-PON) based on chaotic constant composition distribution matching (CCDM). With the implementation of a four-dimensional hyperchaotic Lv system, probabilistic shaping and chaotic…
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Keywords:
chaotic constant;
ofdm pon;
constant composition;
security ... See more keywords