L2 CONSTRAINED SOFTMAX LOSS FOR DISCRIMINATIVE FACE VERIFICATION

Patent №

US 11,636,328

Granted

2023-04-25

Filed 2018

Owner

UNIVERSITY OF MARYLAND, COLLEGE PARK

Lab

AI components

4

ml · nlp · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15938898

Various face discrimination systems may benefit from techniques for providing increased accuracy. For example, certain discriminative face verification systems can benefit from L2-constrained softmax loss. A method can include applying an image of a face as an input to a deep convolutional neural network. The method can also include applying an output of a fully connected layer of the deep convolutional neural network to an L2-normalizing layer. The method can further include determining softmax loss based on an output of the L2-normalizing layer.

Machine learningNatural languageVisionAI hardwareG06V 40/172G06F 17/11G06F 18/2413G06N 3/045G06N 3/0464G06N 3/084G06N 3/09G06N 5/046+3 more

AI classification

Machine learning1.00
Vision1.00
AI hardware1.00
Natural language0.85
Knowledge representation0.06
Speech0.06
Planning0.05
Evolutionary computation0.00

Ownership

UNIVERSITY OF MARYLAND, COLLEGE PARK

assignment · 633470318

Assignors

RANJAN, RAJEEV, CASTILLO, CARLOS, CHELLAPPA, RAMALINGAM

On an employer assignment, the assignors are typically the inventors.

From the same owner

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