Calculation practicing method, system, electronic device and computer readable storage medium

    公开(公告)号:US11521506B2

    公开(公告)日:2022-12-06

    申请号:US16705204

    申请日:2019-12-05

    Abstract: The disclosure provides a calculation practicing method, a system, an electronic device and a computer readable storage medium, the calculation practicing method includes: providing a calculation question; identifying the type and content of the calculation question; generating an answer area according to the type and content of the calculation question; receiving an answering operation in which the user inputs the answer string for the calculation question in the answer area; identifying the answer string inputted by the user; and determining whether each of the answer characters in the answer string is correct, if there is an incorrect answer character, it will be marked, so that the calculation practice can be realized through the electronic device, which is convenient for students to carry out training.

    Examination paper correction method and apparatus, electronic device, and storage medium

    公开(公告)号:US11450081B2

    公开(公告)日:2022-09-20

    申请号:US17425331

    申请日:2020-01-21

    Abstract: An examination paper correction method and apparatus, an electronic device, and a storage medium are provided. The method includes: obtaining a first image of a standard examination paper; identifying an area and characters of each standard answer in the first image, and using a marking box to mark an answering area where each standard answer is located; determining position information of each marking box; obtaining a second image of an examination paper to be corrected; determining, according to the position information of each marking box of the first image, an answering area in the second image matching a position of the marking box, and using a marking box to mark the determined answering area; identifying characters of an answer to be corrected in each marking box of the second image; and comparing the characters of the standard answer with the characters of the answer to be corrected.

    Method and device for generating collection of incorrectly-answered questions

    公开(公告)号:US11410407B2

    公开(公告)日:2022-08-09

    申请号:US17418238

    申请日:2019-12-25

    Abstract: A method and a device for generating a collection of incorrectly-answered questions are provided. The method includes: acquiring an image of a marked test paper (S101); recognizing regions of respective questions in the marked test paper according to a pre-trained first region recognition model (S102); recognizing a question whose marking result is incorrect in the marked test paper as an incorrectly-answered question according to a pre-trained incorrectly-answered question recognition model (S103); and storing the region of the incorrectly-answered question in an incorrectly-answered question database to generate the collection of incorrectly-answered questions (S104). The above solution may solve the problem of low efficiency in generating the collection of incorrectly-answered questions in the prior art.

    Method and system for intelligent identification and correction of questions

    公开(公告)号:US11508251B2

    公开(公告)日:2022-11-22

    申请号:US16580254

    申请日:2019-09-24

    Abstract: A method and a system for intelligent identification and correction of a question, which implements, through artificial intelligence, automatic identification of stems of various types of questions and contents of answering in test papers and auto-corrects the contents of answering. The technical solution is: to train a neural network model (e.g., CNN model) into a model for question type recognition based on numerous test paper samples in advance, and to use this trained model to detect the position of individual questions, the type corresponding to the question, the different components of the question (stem, answer, picture) in the test paper, and then to identify the printed font character information of the stem and the handwriting font character information of the answer part based on the recognition model, and finally to auto-correct based on the identified character information.

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