<?xml version="1.0" encoding="UTF-8"?><resource xmlns="http://datacite.org/schema/kernel-4"><identifier identifierType="URL">https://inrepscholar.com/projects/956</identifier><creators><creator><creatorName>Mingxing Tan, Quoc V. Le</creatorName></creator></creators><titles><title>efficientnet-rethinking-model-scaling-for-convolutional-neural-networks-2022-017</title></titles><publisher>UFTAN UNIVERSITY</publisher><publicationYear>2022</publicationYear><resourceType resourceTypeGeneral="Text">Final Year Project</resourceType><descriptions><description descriptionType="Abstract">This record links to the EfficientNet paper, which proposes compound scaling for convolutional neural network depth, width, and resolution. It supports realistic testing of undergraduate AI project metadata and external PDF handling.</description></descriptions></resource>