Invention Grant
- Patent Title: System for detecting surface type of object and artificial neural network-based method for detecting surface type of object
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Application No.: US17993815Application Date: 2022-11-23
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Publication No.: US11821844B2Publication Date: 2023-11-21
- Inventor: Kun-Yu Tsai
- Applicant: GETAC TECHNOLOGY CORPORATION
- Applicant Address: TW New Taipei
- Assignee: GETAC TECHNOLOGY CORPORATION
- Current Assignee: GETAC TECHNOLOGY CORPORATION
- Current Assignee Address: TW Hsinchu County
- Main IPC: G01N21/88
- IPC: G01N21/88 ; G06N3/08 ; G01J3/28 ; G01N21/956 ; G01N21/952 ; G06T7/586 ; G06T7/00 ; G01N21/3581 ; G06T7/40 ; G06N3/04 ; G06T7/11 ; G06T7/45 ; G06F17/16 ; G06N3/063 ; G01N21/01 ; G06V10/22 ; G06V20/64 ; G06F18/214 ; G06N3/047 ; G06V10/145 ; G06V10/25 ; G06V10/60 ; G06V10/143 ; G06V10/24

Abstract:
An artificial neural network-based method for detecting a surface type of an object includes: receiving a plurality of object images, wherein a plurality of spectra of the plurality of object images are different from one another and each of the object images has one of the spectra; transforming each object image into a matrix, wherein the matrix has a channel value that represents the spectrum of the corresponding object image; and executing a deep learning program by using the matrices to build a predictive model for identifying a target surface type of the object. Accordingly, the speed of identifying the target surface type of the object is increased, further improving the product yield of the object.
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