US 11,810,348 B2
Method for identifying power equipment targets based on human-level concept learning
Yadong Liu, Shanghai (CN); Yingjie Yan, Shanghai (CN); Siheng Xiong, Shanghai (CN); Ling Pei, Shanghai (CN); Zhe Li, Shanghai (CN); Peng Xu, Shanghai (CN); Lei Su, Shanghai (CN); Xiaofei Fu, Shanghai (CN); and Xiuchen Jiang, Shanghai (CN)
Assigned to Shanghai Jiaotong University, Shanghai (CN)
Filed by Shanghai Jiaotong University, Shanghai (CN)
Filed on Mar. 24, 2021, as Appl. No. 17/210,530.
Claims priority of application No. 202010978271.X (CN), filed on Sep. 17, 2020.
Prior Publication US 2022/0083778 A1, Mar. 17, 2022
Int. Cl. G06V 20/20 (2022.01); G06N 3/08 (2023.01); G06F 18/20 (2023.01); G06F 18/2113 (2023.01); G06N 7/01 (2023.01)
CPC G06V 20/20 (2022.01) [G06F 18/2113 (2023.01); G06F 18/29 (2023.01); G06N 3/08 (2013.01); G06N 7/01 (2023.01)] 10 Claims
OG exemplary drawing
 
1. A method for identifying power equipment targets based on human-level concept learning, including:
creating and annotating a dataset of power equipment images;
training a neural network and a Bayesian network with the annotated dataset and respectively acquire identification results and conditional probabilities;
calculating probabilities of unions with the conditional probabilities; and
filtering out the identification result corresponding to the highest probability of the union as an identification result of the dataset of the power equipment images and complete the identification of the power equipment.