	US 12,424,008 B2
	Object recognition processing method, processing apparatus, electronic device, and storage medium
Tao He, Zhejiang (CN); Fan Shi, Zhejiang (CN); Huan Luo, Zhejiang (CN); and Mingquan Chen, Zhejiang (CN)
Assigned to Hangzhou Dana Technology Inc., Zhejiang (CN)
Appl. No. 18/022,523
Filed by Hangzhou Dana Technology Inc., Zhejiang (CN)
PCT Filed Jul. 27, 2021, PCT No. PCT/CN2021/108775 § 371(c)(1), (2) Date Feb. 22, 2023, PCT Pub. No. WO2022/042181, PCT Pub. Date Mar. 3, 2022.
Claims priority of application No. 202010864625.8 (CN), filed on Aug. 25, 2020.
Prior Publication US 2023/0267755 A1, Aug. 24, 2023
Int. Cl. G06V 30/00 (2022.01); G06V 10/82 (2022.01); G06V 30/16 (2022.01)

CPC G06V 30/16 (2022.01) [G06V 10/82 (2022.01)]

13 Claims

1. An object recognition processing method, comprising:

obtaining an object to be recognized;

recognizing a type of the object to be recognized based on a type recognition model;

determining, according to the type of the object to be recognized, a processing rule corresponding to the object to be recognized;

performing, according to the processing rule, a recognition processing on the object to be recognized by means of a transformer learning model, so as to obtain a target result corresponding to the object to be recognized,

wherein the step of performing, according to the processing rule, the recognition processing on the object to be recognized by means of the transformer learning model, so as to obtain the target result corresponding to the object to be recognized comprises:

in response to that the type of the object to be recognized is a basic type, taking, according to the processing rule, the object to be recognized as a target object to be recognized, and in response to that the type of the object to be recognized is a non-basic type, transforming the object to be recognized by means of the transformer learning model according to the processing rule, so as to transform the object to be recognized into the target object to be recognized;

performing the recognition processing on the target object to be recognized by means of the transformer learning model, so as to obtain the target result corresponding to the object to be recognized,

wherein a type of the target object to be recognized is the basic type;

wherein the step of transforming the object to be recognized by means of the transformer learning model, so as to transform the object to be recognized into the target object to be recognized comprises:

in response to that the type of the object to be recognized is calculation-based fill-in-the-blank questions or knowledge-based fill-in-the-blank questions, transforming the object to be recognized into the target object to be recognized directly by means of the transformer learning model;

in response to that the type of the object to be recognized is calculation-based true-false questions, deleting a judgment result from the object to be recognized by means of the transformer learning model, so as to transform the object to be recognized into a first intermediate object to be recognized, and transforming the first intermediate object to be recognized into the target object to be recognized, wherein a type of the first intermediate object to be recognized is the calculation-based fill-in-the-blank questions;

in response to that the type of the object to be recognized is calculation-based multiple-choice questions or knowledge-based multiple-choice questions, deleting respective options from the object to be recognized by means of the transformer learning model, and transforming a question stem in the object to be recognized into the target object to be recognized;

in response to that the type of the object to be recognized is knowledge-based true-false questions, transforming the object to be recognized into a third intermediate object to be recognized by means of the transformer learning model, wherein a type of the third intermediate object to be recognized is the knowledge-based multiple-choice questions, deleting respective options from the third intermediate object to be recognized, transforming a question stem in the third intermediate object to be recognized into a second intermediate object to be recognized, and transforming the second intermediate object to be recognized into the target object to be recognized, wherein a type of the second intermediate object to be recognized is the knowledge-based fill-in-the-blank questions.