本文为芬兰奥卢大学（作者：Hung Dao）的学士论文，共31页。

本文的目的是研究深度学习在卷积神经网络图像分类中的应用。论文采用了基于TensorFlow框架的Python编程语言和Google协作硬件。模型是从网上现有的设计中选择出来的，并由作者进行了调整。经过本文的研究，建立了一个准确、性能良好的模型，但仍有进一步优化的空间。

The objective of this thesis was to study the application of deep learning in image classification using convolutional neural networks. The Python programming language with the TensorFlow framework and Google Colaboratory hardware were used for the thesis. Models were chosen from available ones online and adjusted by the author. After the research, an accurate and performant model was developed and there is still room for further optimization.

1.   引言
   

2. 人工神经网络
3. 卷积神经网络
4. 模型训练与结果
5. 结论

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