Autor:	Soloveitchik, Michael, Werman, Michael
Rok vydání:	2022
Předmět:	Computer Science - Neural and Evolutionary Computing Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We introduce a fully convolutional fractional scaling component, FCFS. Fully convolutional networks can be applied to any size input and previously did not support non-integer scaling. Our architecture is simple with an efficient single layer implementation. Examples and code implementations of three common scaling methods are published.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2203.10670 Zobrazit plný text záznamu View this record from Arxiv