公开(公告)号：US20180107380A1

公开(公告)日：2018-04-19

申请号：US15784766

申请日：2017-10-16

Applicant: Samsung Electronics Co., Ltd.

Inventor： Barath Raj KANDUR RAJA ,  Ankur AGARWAL ,  Chunbae PARK ,  Harshavardhana POOJARI ,  Sungkee KIM ,  Vibhav AGARWAL ,  Youngseol LEE ,  Ishan VAID ,  Raju Suresh DIXIT ,  Dwaraka Bhamidipati SREEVATSA ,  Sanjay KAR ,  Sibsambhu KAR ,  Vanraj VALA ,  Yashwant Singh SAINI

IPC: G06F3/0488 ,  G06F3/041 ,  G06F3/0484

CPC classification number: G06F3/04886 ,  G06F3/0237 ,  G06F3/0416 ,  G06F3/0482 ,  G06F3/04845 ,  G06F3/04883 ,  G06F2203/04808

Abstract: An electronic apparatus for providing an on-screen keyboard including a plurality of keys are provided. The electronic apparatus comprises a touch interface configured to receive a touch input of a user and a processor configured to, in response to the touch input being received though the touch interface, determine a touch area where the touch input is received, in response to the plurality of keys are included in the touch area, identify a key corresponding to a touch pattern of the user among the plurality of keys, and display the identified key on a display of the electronic apparatus.

公开(公告)号：US20210173555A1

公开(公告)日：2021-06-10

申请号：US17111038

申请日：2020-12-03

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Barath Raj KANDUR RAJA ,  Ankur AGARWAL ,  Bharath C ,  Harshavardhana ,  Ishan VAID ,  Kranti CHALAMALASETTI ,  Mritunjai CHANDRA ,  Vibhav AGARWAL

IPC: G06F3/0488 ,  G06N3/04 ,  G06N3/08 ,  G06F17/18

Abstract: Methods and systems for predicting keystrokes using a neural network analyzing cumulative effects of a plurality of factors impacting the typing behavior of a user. The factors may include typing pattern, previous keystrokes, specifics of keyboard used for typing, and contextual parameters pertaining to a device displaying the keyboard and the user. A plurality of features may be extracted and fused to obtain a plurality of feature vectors. The plurality of feature vectors can be optimized and processed by the neural network to identify known features and learn unknown features that are impacting the typing behavior. Thereby, the neural network predicts keystrokes using the known and unknown features.