公开(公告)号：US10795481B2

公开(公告)日：2020-10-06

申请号：US16382702

申请日：2019-04-12

Applicant: Silicon Integrated Systems Corp

Inventor： Tsung-Hua Tsai ,  Ying-Jyh Yeh

IPC: G06F3/041 ,  G06F3/01 ,  G06F3/0488 ,  G06N3/02

Abstract: A method for identifying tap events on a touch panel includes measuring vibration signals for tap events on the touch panel to collect the tap events and record types of the tap events as samples; generating a sample set including a plurality of samples; using the sample set to train a deep neural network to determine an optimized weighting parameter group; taking the deep neural network and the optimized weighting parameter group as a tapping classifier and deploying it to a touch-controlled end product; and obtaining a predicted tap type based on a vibration signal and an image formed by touch sensing values detected by the touch-controlled end product to which a tap operation is performed. The present disclosure also provides a system corresponding to the identifying method, and a touch-controlled end product.

公开(公告)号：US11287903B2

公开(公告)日：2022-03-29

申请号：US16262291

申请日：2019-01-30

Applicant: Silicon Integrated Systems Corp.

Inventor： Tsung-Hua Tsai ,  Ying-Jyh Yeh

IPC: G06F3/0346 ,  G06F3/041 ,  G06F3/0354 ,  G05B13/00 ,  G06N3/02

Abstract: A novel method is proposed to operate a stylus product. In this method, inertial measurement unit (IMU) signals are used to estimate a tilted angle of the stylus product. On the other hand, acceleration signals measured when a finger taps a stylus are collected to train a deep neural network as a tap classifier. A combination of the tilted angle and the tap classifier allows a user to interact with a peripheral device (e.g. a touchscreen) by rotating and taping the stylus product. A tap classifying system and a stylus product are also provided.

公开(公告)号：US20190138151A1

公开(公告)日：2019-05-09

申请号：US16179095

申请日：2018-11-02

Applicant: Silicon Integrated Systems Corp.

Inventor： Tsung-Hua Tsai ,  Jing-Jyh Yeh

IPC: G06F3/041 ,  G06F3/0488 ,  G06N3/08

Abstract: A method for classifying tap events on a touch panel includes collecting the tap events on the touch panel and recording the type of each of the tap events as a sample; generating a sample set including a plurality of the samples; using the sample set to train a deep neural network to determine an optimized weighting parameter group; taking the deep neural network and the optimized weighting parameter group as a tapping classifier and deploying it in a touch panel product. The present disclosure also provides a system corresponding to the classifying method, and a touch panel product.