What is color augmentation?

The term PCA Color Augmentation refers to a type of data augmentation technique first mentioned in the paper titled ImageNet Classification with Deep Convolutional Neural Networks. Specifically, PCA Color Augmentation is designed to shift those values based on which values are the most present in the image.

What is the PCA meaning?

PCA: Commonly used abbreviation for patient-controlled analgesia. Analgesia simply means relief of pain. PCA is a method by which the patient controls the amount of pain medicine (analgesia) they receive. Studies have shown that patients using PCA often use less morphine than do patients who are not on PCA.

What is augmentation in image processing?

What is Image Augmentation? Image augmentation is a technique of altering the existing data to create some more data for the model training process. In other words, it is the process of artificially expanding the available dataset for training a deep learning model.

What is data augmentation explain technique of data augmentation?

Data augmentation is the technique of increasing the size of data used for training a model. For reliable predictions, the deep learning models often require a lot of training data, which is not always available. Therefore, the existing data is augmented in order to make a better generalized model.

What is data augmentation give some examples?

What are use cases/examples in data augmentation? Image recognition and NLP models generally use data augmentation methods. Also, medical imaging domain utilizes data augmentation to apply transformations on images and create diversity into the datasets.

What does data augmentation mean?

Data augmentation in data analysis are techniques used to increase the amount of data by adding slightly modified copies of already existing data or newly created synthetic data from existing data. It acts as a regularizer and helps reduce overfitting when training a machine learning model.