基于深度学习的机器视觉:垃圾分类. 完整代码+报告

上传者: 55771290 | 上传时间: 2023-03-10 13:22:26 | 文件大小: 17.28MB | 文件类型: ZIP
本次实验提供六个类别的垃圾识别分类数据集,分别是glass、cardboard、metal、paper、plastic、trash。本次实验是基于卷积神经网络模型来完成六个类别垃圾分类。 目前垃圾分类已经在许多城市开展起来。这看似微不足道的“小事”,实则关系到13亿多人生活环境的改善,理应通过人工智能技术来大力提倡社会风气养成。本次实验提供六个类别的垃圾识别分类数据集,分别是glass、cardboard、metal、paper、plastic、trash。本次实验是基于卷积神经网络模型来完成六个类别垃圾分类。 2.任务要求 每位同学单独完成;建立神经网络模型,并尽可能将其参数调优到最佳状态;绘制深度学习模型图、绘制并分析学习曲线等;分析模型并试着调试不同学习率等超参数对模型的结果影响 ;使用Python语言。 3.实验方法 卷积神经网络 (Convolutional Neural Network, CNN)是一种结构类似于人类或动物的 视觉系统 的人工神经网络,包含一个或多个卷积层(Convolutional Layer)、池化层(Pooling Layer)和全连接层(Full

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