Deep learning (DL) has gained a lot of popularity in the science and business community. It has been successful in a range of applications, especially in computer vision. This paper presents results from applying scaled MNIST images dataset to a popular implementation of deep learning called ResNet. This is a valuable contribution because in general convolutional networks are not scale invariant. Our objective is to explore the behavior of a residual neural network when trained and evaluated using three different datasets of scaled MNIST images.
|Title of host publication||ICBDE'19|
|Subtitle of host publication||Proceedings of the 2019 International Conference on Big Data and Education|
|Number of pages||5|
|Publication status||Published - 30 Mar 2019|
- feature cnn
- machine learning
- deep learning