-
公开(公告)号:US20210059511A1
公开(公告)日:2021-03-04
申请号:US16774279
申请日:2020-01-28
Applicant: Quanta Computer Inc.
Inventor: Kai-Ju CHENG , Hsin-Lun HSIEH , Chin-Yuan TING , Tsung-Hsin LU , Huan-Tang WU , Shao-Ang CHEN , Yu-Hsun CHEN , Jia-Chyi WANG , Chih-Wei SUNG , Huan-Pin SHEN
Abstract: A method for distinguishing plaque and calculus is provided. The method is used in a device and includes the following steps: emitting, by a blue light-emitting diode, blue light to illuminate teeth in an oral cavity, wherein the blue light is used to generate autofluorescence of plaque and calculus on the teeth; sensing, by an image sensor, the autofluorescence of plaque and calculus; and distinguishing, by a processor, a plaque area and a calculus area on the teeth based on the autofluorescence.
-
公开(公告)号:US20200090639A1
公开(公告)日:2020-03-19
申请号:US16242325
申请日:2019-01-08
Applicant: Quanta Computer Inc.
Inventor: Yi-Ling CHEN , Chih-Wei SUNG , Yu-Cheng CHIEN , Kuan-Chung CHEN
Abstract: The speech correction system includes a storage device, an audio receiver and a processing device. The processing device includes a speech recognition engine and a determination module. The storage device is configured to store a database. The audio receiver is configured to receive an audio signal. The speech recognition engine is configured to identify a key speech pattern in the audio signal and generate a candidate vocabulary list and a transcode corresponding to the key speech pattern; wherein the candidate vocabulary list includes a candidate vocabulary corresponding to the key speech pattern and a vocabulary score corresponding to the candidate vocabulary. The determination module is configured to determine whether the vocabulary score is greater than a score threshold. If the vocabulary score is greater than the score threshold, the determination module stores the candidate vocabulary corresponding to the vocabulary score in the database.
-
公开(公告)号:US20210074011A1
公开(公告)日:2021-03-11
申请号:US16707234
申请日:2019-12-09
Applicant: Quanta Computer Inc.
Inventor: Kai-Ju CHENG , Kuan-Chung CHEN , Yu-Cheng CHIEN , Chung-Sheng WU , Hao-Ping LEE , Chin-Yuan TING , Yu-Hsun CHEN , Shao-Ang CHEN , Jia-Chyi WANG , Chih-Wei SUNG
Abstract: A tooth-position recognition system includes an electronic device and a calculation device. The electronic device includes a first camera. The first camera is configured to capture a plurality of tooth images. The calculation device includes a second camera and a processor. The second camera is configured to capture a user image. The processor is configured to receive the tooth images, compare the corresponding position of each pixel in each tooth image to generate a depth map, and input the tooth images, the depth map, and a plurality of first tooth-region identifiers into a tooth deep-learning model. The tooth deep-learning model outputs a plurality of deep-learning probability values that are the same in number as the first tooth-region identifiers. The processor inputs the user image and the plurality of second tooth-region identifiers into a user-image deep-learning model.
-
-