Tvarit Gmbh

Rishabh Agrahari

Rushil Gupta

Nihal Rajan Barde

Prathosh Ap

Aditya Srivastava

Arnab Kumar Mondal

Kamal Galrani

Naga Sai Pranay Modukuru

Sanjay Shekhawat

Rahul Prajapat

Sachin Kumar

A cross domain generalization system for industrial artificial intelligence (AI) applications is disclosed. A target encoder subsystem obtains target data from a target machine product and generates lower dimensional data for obtained target data using a target artificial intelligence (AI) model. The generated lower dimensional data are corresponding to a plurality of target embeddings data. The target encoder subsystem further applies the plurality of target embeddings data into a source classifier AI model. A source classifier subsystem predicts a quality of the target machine product by generating class labels for each of the plurality of target embeddings data based on a result of the classifier AI model. The goal of the present invention is to learn features or representations such that the correlation with a label space is similar both in source and target domains while being invariant of data distributions.

System and method for cross domain generalization for industrial artificial intelligence applications class

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Mumbai, India

Rishabh Agrahari