作者
Victoria Ruiz, Ángel Sánchez, José F Vélez, Bogdan Raducanu
发表日期
2019
研讨会论文
From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II 8
页码范围
422-431
出版商
Springer International Publishing
简介
The management of solid waste in large urban environments has become a complex problem due to increasing amount of waste generated every day by citizens and companies. Current Computer Vision and Deep Learning techniques can help in the automatic detection and classification of waste types for further recycling tasks. In this work, we use the TrashNet dataset to train and compare different deep learning architectures for automatic classification of garbage types. In particular, several Convolutional Neural Networks (CNN) architectures were compared: VGG, Inception and ResNet. The best classification results were obtained using a combined Inception-ResNet model that achieved 88.6% of accuracy. These are the best results obtained with the considered dataset.
学术搜索中的文章
V Ruiz, Á Sánchez, JF Vélez, B Raducanu - From Bioinspired Systems and Biomedical Applications …, 2019