matlab最简单的代码-cnn_fruits_examples:基于CNN的水果分类示例(本文代码https://doi.org/10.33

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matlab最简单的代码基于CNN的水果分类示例 这些代码是作为论文“卷积神经网络应用于水果图像处理的回顾”,Applied Sciences,10(10):3443(2020)的一部分而实现的。 为了说明使用一些可用工具来开发CNN的方法,我们展示了水果分类和质量控制示例的实现。 另外,使用众所周知的预训练模型实现了相同的示例,以便说明使用转移学习的另一种解决方案。 重要的是要记住,这些示例的目的只是以最简单的方式显示如何针对特定任务实现CNN模型。 因此,建议的示例未进行优化,因此提出了非常简单的解决方案,以使其易于理解。 为了便于比较和讨论,您可以阅读我们的论文。 分别使用TensorFlow [99]和深度学习工具箱[102]在Python和MATLAB中对实现进行了编码。 对源代码进行了注释,并提供了描述性信息,也可以在我们的实验室LITRP()网站上在线获得这些代码。 如何引用 请随时使用我们的代码并按如下方式引用我们: 纳兰霍-托雷斯(J. 莫拉(Mora); Hernández-García,河; 巴里恩托斯(RJ); 弗雷德斯角; Valenzuela,A。卷积神经网

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