Invention Grant
- Patent Title: Validation of deep neural network (DNN) prediction based on pre-trained classifier
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Application No.: US16830563Application Date: 2020-03-26
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Publication No.: US11461650B2Publication Date: 2022-10-04
- Inventor: Ripon K Saha , Mukul R Prasad , Seemanta Saha
- Applicant: FUJITSU LIMITED
- Applicant Address: JP Kawasaki
- Assignee: FUJITSU LIMITED
- Current Assignee: FUJITSU LIMITED
- Current Assignee Address: JP Kawasaki
- Agency: Fujitsu Patent Center
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F16/28 ; G06F16/55

Abstract:
According to an aspect of an embodiment, operations may include receiving a first data point associated with a real-time application and predicting a first class for the received first data point, by a Deep Neural Network (DNN) pre-trained for a classification task of the real-time application. The operations may further include extracting, from the DNN, a first set of features and a corresponding first set of weights, for the predicted first class. The extracted first set of features may be associated with a convolution layer of the DNN. The operations may further include determining, by a pre-trained classifier associated with the predicted first class, a confidence score for the predicted first class based on the extracted first set of features and the corresponding first set of weights. The operations may further include generating output information to indicate correctness of the predicted first class based on the determined confidence score.
Public/Granted literature
- US20210303986A1 VALIDATION OF DEEP NEURAL NETWORK (DNN) PREDICTION BASED ON PRE-TRAINED CLASSIFIER Public/Granted day:2021-09-30
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