Increase ACCURACY of Model on Small Dataset | DATA AUGMENTATION for Small Image Dataset

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This video titled "Increase ACCURACY of Model on Small Dataset | DATA AUGMENTATION for Small Image Dataset" explains the concept of Data Augmentation API of Keras Framework known as ImageDataGenerator(). One can achieve greater accuracy on a deep learning neural network such as Convolutional Neural Network even if he/she has very small subset of Image data or a very small number of image data. This video also covers Data Augmentation using Python Language which is a heavily used concept in computer vision and is used for building Object Detection, Face Recognition, Self Driving Cars, Motion Tracking, etc. If we want to build a more accurate model then we need to have loads and loads of data. Be its image data, text data, or even transaction data. The more the data we have for training purpose the better prediction we will get from our deep learning or machine learning model. Also, the chances of model overfitting will also get increased when we have a smaller datasets. So If have a small dataset with fewer images then we can create variations of that image data.

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State True or False : ImageDataGenerator() saves the augmented images first in the computer storage and then performs model training

TheAIUniversity

Can you please drop the code snippet to use this technique on more than 1 images (probably hundreds of images) in a single execution.

harshtyagi

Sir, does the annotation files with (class id, and size of the box ) have to be generated manually, or does the tool can generate the txt files

elrayoauto

Hello, could you plz help in applying this on cifar10?

chirellehage

How can we augment the corresponding mask with ssme ratio.

tasleemmustafa

How can count the number of new dataset After data augmentation?

_ishraqaldagamseh

how to do it hundreds of images in single execution

mohitgupta-xyek

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