Automated identification of cephalometric landmarks: Part 1—Comparisons between the latest deep-learning methods YOLOV3 and SSD

OBJECTIVE: To compare the accuracy and computational efficiency of two of the latest deep-learning algorithms for automatic identification of cephalometric landmarks. MATERIALS AND METHODS: A total of 1028 cephalometric radiographic images were selected as learning data that trained You-Only-Look-On...

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Bibliografiska uppgifter
I publikationen:Angle Orthod
Huvudupphovsmän: Park, Ji-Hoon, Hwang, Hye-Won, Moon, Jun-Ho, Yu, Youngsung, Kim, Hansuk, Her, Soo-Bok, Srinivasan, Girish, Aljanabi, Mohammed Noori A., Donatelli, Richard E., Lee, Shin-Jae
Materialtyp: Artigo
Språk:Inglês
Publicerad: Edward H. Angle Society of Orthodontists 2019
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Original Articles
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC8109157/
https://ncbi.nlm.nih.gov/pubmed/31282738
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2319/022019-127.1
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