Patent · US Active

Synthetic rare class generation by preserving morphological identity

US11531830B2 · kind B2 · utility

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8Claims

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Assignee

Tata Consultancy Services Limited · IN

Inventors

Arijit Ukil · Sherghati, IN
Soma Bandyopadhyay · Sherghati, IN
Chetanya Puri · Sherghati, IN
Rituraj Singh · Sherghati, IN
Arpan Pal · Sherghati, IN

Key dates

Filing date	Aug 13, 2018
Grant date	Dec 20, 2022
Priority date	—
Expiry date	Oct 21, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG16C20/70
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

In many real-life applications, ample amount of examples from one class are present while examples from other classes are rare for training and learning purposes leading to class imbalance problem and misclassification. Methods and systems of the present disclosure facilitate generation of an extended synthetic rare class super dataset that is further pruned to obtain a synthetic rare class dataset by maximizing similarity and diversity in the synthetic rare class dataset while preserving morphological identity with labeled rare class training dataset. Oversampling methods used in the art result in cloning of datasets and do not provide the needed diversity. The methods of the present disclosure can be applied to classification of noisy phonocardiogram (PCG) signals among other applications.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.