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Multi-label Garbage Image Classification Based on Deep Learning

机译:基于深度学习的多标签垃圾图像分类

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摘要

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.
机译:近年来,随着深度学习技术的发展,图像识别的准确性得到了显着改善。深度学习已广泛用于识别单标签图像。该项目旨在智能地将家庭垃圾图像分类为基于深度的应用场景。学习对包含多个视觉物体的图像进行多标签分类研究,并设计和构建多标签垃圾图像分类模型,以提高识别准确性和速度作为对多标签垃圾图像进行分类研究的主要研究目标。

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