Deep Learning Approaches towards Book Covers Classification

被引：4

作者：

Buczkowski, Przemyslaw ^{[1
,2
]}

Sobkowicz, Antoni ^{[2
]}

Kozlowski, Marek ^{[1
]}

机构：

[1] Natl Informat Proc Inst, Warsaw, Poland

[2] Warsaw Univ Technol, Warsaw, Poland

来源：

PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS (ICPRAM 2018) | 2018年

关键词：

Image Classification; Convolutional Neural Networks; Pattern Recognition; Deep Learning; Machine Learning; Supervised Learning; Artificial Intelligence;

D O I：

10.5220/0006556103090316

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Machine learning methods allow computers to use data in less and less structured form. Such data formats were available only to humans until now. This in turn gives opportunities to automate new areas. Such systems can be used for supporting administration of big e-commerce platforms e.g. searching for products with inadequate descriptions. In this paper, we continue to try to extract information about books, but we changed the domain of our predictions. Now we try to make guesses about a book based on an actual cover image instead of short textual description. We compare how much information about the book can be extracted from those sources and describe in detail our model and methodology. Promising results were achieved.

引用

页码：309 / 316

页数：8