The article demonstrates how to do data augmentation to increase the size of the data. We will first build a deep learning model without performing augmentation and will compute the accuracy. After ...

Learn how to use data augmentation to improve your CNN image classification models. Avoid common pitfalls and follow best practices for choosing, applying, evaluating, and optimizing data ...

In this project , we will look into one such image classification problem namely Flower Species Recognition, which is a hard problem because there are millions of flower species around the world. As ...

Building data input pipelines using the tf.keras.preprocessing.image.ImageDataGenerator class to efficiently work with data on disk to use with the model. Overfitting —How to identify and prevent it.

Then, through randomly sampling the coefficient in the data mixture model, we obtain several independent classifiers and fuse them with a voting strategy to produce the final classification results.

Data augmentation is a widely used regularization technique for improving the performance of convolutional neural networks (CNNs) in image classification tasks. To improve the effectiveness of data ...

Perez, L. and Wang, J. (2017) The Effectiveness of Data Augmentation in Image Classification Using Deep Learning. ArXiv: 1712.04621. has been cited by the following article: TITLE: Building Detection ...