Efficient CNN Models for Beer Bottle Cap Classification Problem

Autor:	Tai Huynh, Linh Nguyen, Hai H. Vo, Vuong T. Pham, Quan M. Tran
Rok vydání:	2019
Předmět:	Work (electrical) Computer science business.industry Deep learning Bottle cap Artificial intelligence business Convolutional neural network Residual neural network
Zdroj:	Future Data and Security Engineering ISBN: 9783030356521 FDSE
DOI:	10.1007/978-3-030-35653-8_51
Popis:	In this work, we present an efficient solution to the beer bottle cap classification problem. This problem arises in the Wecheer smart opener project. Although classification problem is common in Computer Vision, there is no dedicated work for beer bottle cap dataset. We combine state-of-the-art deep learning techniques to solve the problem. Our solution outperforms the well-known commercial system that is currently used by the Wecheer project. It is also more efficient than the famous architectures such as VGG, ResNet, and DenseNet for our purposes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::27d5405ab7f5862306b6c467d1b8acf2 https://doi.org/10.1007/978-3-030-35653-8_51 Zobrazit plný text záznamu