Questions tagged [data-augmentation]

For questions related to the concept of data augmentation, where a dataset can be augmented in terms of number and diversity of the samples, which can be useful to avoid over-fitting, especially, when the available dataset(s) is relatively small.

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18 views

Batch normalization for multiple datasets?

I am working on a task of generating synthetic data to help the training of my model. This means that the training is performed on synthetic + real data, and tested on real data. I was told that batch ...
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2answers
32 views

Train Validation Test Splitting After or Before Data Augmentation?

I have seen tutorials online saying that you should do data augmentation AFTER doing the train/val/test split. However, when I go online to read some research papers, I see numerous instances of ...
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What image augmentations can help a neural network identify the smallest pixels within an image?

I am training a CNN to identify objects and I believe the network will learn much faster if it can learn to focus on the smallest pixels. One way to go about this would be to augment the images before ...
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19 views

Could an adaptive discriminator augmentation (ADA) be used for a discriminatory task?

Was wondering if I could use an adaptive discriminator augmentation (ADA) on a data set like MNIST (multi-class classification task). It seems that this is focused on generative modeling, so not sure ...
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1answer
32 views

Data augmentation for very small image datasets

I am looking for techniques for augmenting very small image datasets. I have a classification problem with 3 classes. Each class consists of 20 different shapes. The shapes are similar between the ...
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0answers
11 views

Does distribution of data augmentation parameters matter?

Idea Let's say we have simple pictures dataset containing 40x40 images of digits. We have only one image of each digit. We want to use that as training set, but we need more data, so we use data ...
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2answers
53 views

Is creating dataset only by augmentation a bad practice?

I wonder if creating data set only by augmentation base images is a bad practice. I mean the situation when you have to train net to predict really simple patterns, for example printed-like digits. ...
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1answer
28 views

Should one rescale (normalize) image before or after data augmentation?

During image preprocessing pipeline, should one rescale each pixel value to [0, 1] by dividing 255 first, and then perform data transformation such as color distortion, gaussian blur? or vice versa? I ...
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5answers
70 views

How do I increase the size of an (almost) balanced dataset?

I am trying to add more data points in my (almost) balanced dataset for training my neural network. I have come across techniques such as SMOTE or Random Over Sampling, but they work best for ...
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1answer
95 views

What is the difference between feature extraction with or without data augmentation?

Here's an extract from Chollet's book "Deep Learning with Python" about using pre-trained CNN to predict class from a photo set (p. 146): At this point, there are two ways you could proceed:...
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1answer
36 views

Late Onset Augmentation

If I train a U-Net model for image segmentation (e.g. medical images) and start training until it converges and then add augmentation - can i expect similar results as if i train with augmentation ...
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18 views

How to augment 2.5D keypoints?

I am currently working on 3D hand pose estimation. The idea is to first detect the 2.5D pose representation and then obtain 3D pose with the help of camera parameters. For some reason, I was trying to ...
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35 views

Data Augmentation of store images using handwritten labels

I am new to AI and NN. I've started learning using Geron's book on Tensorflow. My first project ("Smart Shelf") is to determine which items in a store have been purchased and need refilled. ...
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40 views

Is there any rule of thumb to determine the amount of data needed to train a CNN

I am training an AlexNet Convolutional Neural Network to classify images in a dataset. I want to know if there is any general rule for using data augmentation in training a neural network. How can I ...
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18 views

How to perform data augmentation on multiple input classification task?

I would like to add some more samples to my dataset which consists of two parts: 1. image and 2. numerical data. For each image in the dataset there is its corresponding numerical data as well. If it ...
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0answers
28 views

If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?

When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations. If random rotations are added, how is the new bounding box calculated?
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1answer
47 views

Should I remove the text overlaying some images in the dataset before training the CNN?

If I am attempting to train a CNN on some image data to perform image classification, but some of the images have pieces of text overlaying them (for the purpose of description to humans), then is it ...
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0answers
78 views

How much should we augment our training data?

I am wondering how much I should extend my training set with data augmentation. Is there somewhere a pre-defined number I can go with? Suppose I have 10000 images, can I go as far as 10x or 20x times, ...
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0answers
52 views

What is the amount of test data needed to evaluate a CNN?

I have an image dataset of about 400 images. 70% of these data points were used for training, 15% for validation, and 15% for testing. I am using the 70% to train a CNN-based binary classifier. I ...
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1answer
80 views

Do I need to rotate the masks, if I also rotate the images and the masks are generated from the input?

I am training a neural network that takes an input (H, W, 3) and has the output of size (H', W', C). Now, to augment my dataset, ...
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1answer
45 views

What could cause a big fluctuation of the loss in the last epochs of training an AlexNet?

I am training an AlexNet neural network, with about 12000 images which 80% is for training, 10% is for validation and another 10% is for testing. I have a problem in my plots. There is a big ...
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1answer
90 views

Validation Loss Fluctuates then Decrease alongside Validation Accuracy Increases

I was working on CNN. I modified the training procedure on runtime. As we can see from the validation loss and validation accuracy, the yellow curve does not fluctuate much. The green curve and red ...
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1answer
1k views

How to label edited images after data augmentation?

I am new to neural networks, I've only started studying and learning about the subject a year ago, and I just started building my first neural network. The project is a little bit ambitious: A browser ...
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3answers
191 views

Would this relatively small dataset be enough to train a CNN?

Scenario: I am trying to create a dataset with images of choice for different animal classes. I am going to train those images for classification using CNN. Problem: Let's assume I somehow don't have ...