Work

Tradeoffs in Data Augmentation: An Empirical Study

Year: 2021

Type: conference-paper

Source: International Conference on Learning Representations

Authors: Raphael Gontijo-Lopes, Sylvia Smullin, Ekin D. Cubuk, Ethan Dyer

Institutions: Google (United States), Stanford University

Language: English

Topic: Domain Adaptation and Few-Shot Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W3130325649

FWCI: 2.727

Cites: 56

Cited by: 34

Related to: 10