2019
DOI: 10.1109/tcyb.2017.2772289
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Tooth-Marked Tongue Recognition Using Multiple Instance Learning and CNN Features

Abstract: Tooth-marked tongue or crenated tongue can provide valuable diagnostic information for traditional Chinese Medicine doctors. However, tooth-marked tongue recognition is challenging. The characteristics of different tongues are multiform and have a great amount of variations, such as different colors, different shapes, and different types of teeth marks. The regions of teeth mark only appear along the lateral borders. Most existing methods make use of concave regions information to classify the tooth-marked ton… Show more

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Cited by 65 publications
(79 citation statements)
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“…The first is the result on five-fold cross-validation, which is used to evaluate the performance of the proposed method. The second is the comparison with other works, such as Shao et al [19] and Li et al [6].…”
Section: Experiments and Discussionmentioning
confidence: 84%
See 4 more Smart Citations
“…The first is the result on five-fold cross-validation, which is used to evaluate the performance of the proposed method. The second is the comparison with other works, such as Shao et al [19] and Li et al [6].…”
Section: Experiments and Discussionmentioning
confidence: 84%
“…Recently, some researchers have used CNN features to extract tooth-marked features. In [6], a method for extracting features using CNN, using a multi-instance classifier for final classification, was proposed.…”
Section: Tongue Diagnosismentioning
confidence: 99%
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