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 ...

We explore and compare multiple solutions to the problem of data augmentation in image classification. The work has demonstrated the effectiveness of data augmentation through simple techniques, such ...

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 ...

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.

Cibaca continues to explore image classification and deep learning from a research-first perspective. Her ongoing work ...

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 ...