基于深度学习的多标签垃圾图像分类

Kang Yan, Wenyu Si, Jin Hang, Hong Zhou, Quanyin Zhu
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引用次数: 4

摘要

近年来,随着深度学习技术的发展,图像识别的准确率得到了显著提高。深度学习在单标签图像识别中得到了广泛的应用。本项目旨在对生活垃圾图像进行深度智能分类为应用场景。学习对包含多个视觉对象的图像进行多标签分类研究,设计并构建多标签垃圾图像分类模型,以提高识别精度和速度为主要研究目标,对多标签垃圾图像进行分类研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-label Garbage Image Classification Based on Deep Learning
In recent years, with the development of deep learning technology, the accuracy of image recognition has been significantly improved. Deep learning has been widely used in the recognition of single-label images. This project aims to intelligently classify domestic garbage images as application scenarios based on depth. Learn to carry out multi-label classification research on images containing multiple visual objects, and design and build a multi-label garbage image classification model to improve recognition accuracy and speed as the main research goal to conduct classification research on multi-label garbage images.
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