Questions tagged [data-augmentation]

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Fastest batch perspective transform for image augmentation

I need to do some augmentation for my training images for a neural networks. The problem is that even when loading batches in parallel, the augmentation is taking longer to perform than the network ...
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Random crop in multi-label image classification context

In some research papers, people use random cropping with variable sizes and then they resize them to original size as a data augmentation technique saying that it helps boost results. Can someone help ...
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30 views

Data Augmentation techniques for classification of imbalanced time series datasets

Now I have a task to classify the imbalanced time series datasets using ML classifiers, such as Logistic Regression, Decision Tree, SVM, and KNN. I am not allowed to use the Deep Learning tools, such ...
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How do I augment data after spliting traininng datset into train and validation set for CIFAR10 using PyTorch?

When classifying the CIFAR10 in PyTorch, there are normally 50,000 training samples and 10,000 testing samples. However, if I need to create a validation set, I can do it by splitting the training set ...
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1answer
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What is the reason behind having low results using the data augmentation technique in NLP?

I used Data augmentation technique on my dataset, to have more data to train. My data is text so the data augmentation technique is based on random insertion of words, random swaps and synonyms ...
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45 views

Data Augmentation Multi Outputs

This question is asked several times here on SE, but I havent been able to find the right answer. I'm trying to build a network with 1 input and 2 outputs. I don't have a lot of data so I would like ...
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1answer
20 views

Using data agumentation for a frozen pre-trained model

I was following the following article with regards to doing transfer learning: https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html In the section, Using ...
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1answer
36 views

Non-Real Time Data Augmentation for CNN Classification. What are the drawbacks?

When people talk about and use data augmentation, are they mostly referring to real-time data augmentation? In the case of image classification, that would involve augmenting the data right before ...
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2answers
60 views

after augmentation validation accuracy going down?

My main question is about augmentation. if I process the augmentation I believe it always better than less data but in my case the validation accuracy going down train : 7000 images , validation: ...
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24 views

Can the test set of non-image data be augmented?

I have learned the test set of image data can be augmented by a method called Test Time Augmentation and I am wondering after I researched on it if the test set of ...
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20 views

Back-Translation model for German and English

Do you know of any pre-trained models for back translation between German and English? I am aware that there are ways to include a monolingual corpus into the training of a machine translation model (...
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1answer
93 views

Why can't I use data augmentation with a pretrained convnet?

Reading Deep Learning with Python by François Chollet. In section 5.3.1, we've instantiated a pretrained convnet, VGG16, and are given two options to proceed: A) Running the convolutional base over ...
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How to return batches of augmented images in an image preprocessor?

I've written the following class that generates augmented images one by one. However, I'd like to be able to generate batches of 8 images each (or any number really). The way I'm hoping to do it is: ...
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1answer
108 views

Is image sharpening a good idea for data augmentation?

I'm training segmentation networks and while the dataset is somehow decent (~5k images) I wanted to augment it, so far I'm trying: RandomFlip RandomRotate RandomBrightness changes RandomShadows Due ...
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188 views

Implementing back translation as a data augmentation for text classification

Since back translation English->other language -> English seems like quite a useful data augmentation technique , I wanted to experiment with it. E.g. it occurred to me that languages from very ...
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2answers
731 views

Is there any augmentation tool for images and bounding boxes?

I don't have a lot of training data and I'm looking for some tools in python or executable program like labelimg that do some heavy augmentation on images, even better if they also change bounding ...
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1answer
1k views

CNN - imbalanced classes, class weights vs data augmentation

I have a set of data with a few strongly imbalanced classes, eg the smallest class is about 54 times smaller than the largest. Therefore, data augmentation in order to equalize the size of classes ...
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9 views

Is it good in general to subtract background from a sequence of images for learning?

Context: I have a sequence of satellite images, indexed by time, so basically it's a video. Images were taken on top of a mountain, to capture a main cause that affects solar rays. (GHI in other ...
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438 views

How to properly rotate image and labels for semantic segmentation data augmentation in Tensorflow?

What's a proper procedure for doing the image and label rotation for semantic segmentation in dataset augmentation using Tensorflow? Images I have seen the function tf.contib.image.rotate(), but ...
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2answers
97 views

Is there a disadvantage to letting a model train for a large number of epochs?

I created a model to solve a time series forecasting problem. I had a limited amount of time series with which I could train the model therefore I decided to augment the data. The data augmentation ...
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1answer
22 views

Generated training set on convnet

I have a dataset with roughly 800 images that are classified in 18 classes. The classes are spread unevenly, with some classes having 30 images and others having 5. In order to increase my dataset,...
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1answer
272 views

How to benefit Data augmentation when it yields to different classes

I'm trying to classify rooftop sky images orientations, whether it is horizontal or vertical. Knowing that the most obvious feature here is known: orientation. I can simply augment each class by ...
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1answer
43 views

What brings the performance difference in Deep Learning with different data augmentation strategies?

I am studying the performance of deep learning models toward abnormality detection in chest X-rays. Due to sparsity of data, I augment the data using different augmentation strategies including: ...
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1answer
55 views

Methods for augmenting binary datasets

I have a small (~100 samples) dataset with roughly 20 features which are mostly binary, and a few are numeric (~5). I wanted to use methods for augmenting the training set and see if I can get better ...
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2answers
387 views

When using Data augmentation is it ok to validate only with the original images?

I'm working on a multi-classification deep learning algorithm and I was getting big over-fitting: My model is supposed to classify sunglasses on 17 different brands, but I only had around 400 images ...
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3answers
984 views

How can I augment my image data?

What are the correct and common ways to normalize image for CNN? I used to work with text and it was pretty straightforward. Removing stop words, clean text from noise, tokenization, stemming etc. ...
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1answer
112 views

Data Augmentation for Regression ANN with low Sample Size

There is a Dataset of 65 tuples. I want to Augment new Data from this set and validate my ANN on the original Data. Is there a possibility, that my ANN already overfits on the augmentet Data. For ...
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144 views

Data augmentation / feature extraction on pre-trained convnets

I'm reading 'Deep Learning with Python' by François Chollet, which is an excellent book. He talks about using pre-trained convnets (in his example, VGG16) and then running smaller datasets to tweak ...
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2answers
2k views

Data Augmentation recommended pipeline

I want to perform image classification using Keras and a dataset made of 50 classes. At the moment, I have only 7 images per class and I need to perform data augmentation in order to train the model ...
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1answer
1k views

How to create speech commands data set

I am planning to create a speech recognition network that recognize few words (voice commands) and came across Speech Commands dataset from google. Apart from available dataset I am planning to add ...
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1answer
116 views

GAN's for data augmentation [closed]

I am working to augment my data using Generative Adversarial Networks, I have used Deep Convolutional GAN's for this purpose but they are not learning the right data distribution, so please suggest me ...
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193 views

Expected behaviour of loss and accuracy when using data augmentation

I have implemented a convolutional neural network in Keras, and I use off-line data augmentation in the training set. The way I do this is that I create batches of training data in separate files (...
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0answers
204 views

Spatial Transformer Networks and Data Augmentation

We are all familiar with the famous Deep Mind paper STN. Upon implementation, such as https://pytorch.org/tutorials/intermediate/spatial_transformer_tutorial.html , did anyone still use input data ...
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1answer
3k views

Memory error on using data generator in keras

I am using the following augmentations on dataset of size 9 GB: ...
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150 views

Data augmentation from directory and oriented features with Keras

Let this, be a dataset labeling the head pose for each photo: ...
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1answer
988 views

How to implement PCA color augmentation as discussed in AlexNet

I read through "ImageNet Classification with Deep Convolutional Neural Networks" again specifically for details on how to implement PCA color augmentation. I am unsure if I have it right. Here is how ...
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1answer
2k views

Data augmentation: rotating images and zero values

A lot of people rotate images to create a larger training set for neural networks. For most nets, all of the inputs have to be the same size so the image rotation function has to crop the newly ...
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747 views

Is image data augmentation breaking the distribution?

NOTE: if you can please edit my question title... I am thinking a simple question just came in my mind. There are many people use data augmentation on their image data to train deep CNN. When I ...
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Are annotated audio datasets augmented with mutated versions the way image datasets are?

Data augmentation is very standard for annotated image datasets for tasks like image labelling. Images are flipped, rotated, pixelated and so on, to add more training data and make the system robust ...
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2answers
1k views

Data Augmentation for Regression

I want to use deep learning for regression. However, the number of training samples is not large. In image processing, some new samples are generated on the basis of initial data through tasks like ...
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2k views

Data Augmentation in Tensorflow

I am trying to replicate a network for facial key point detection like in the following link Daniel Nouri's Blog on KFKD. The blog uses Lasagne but i am trying to do using Tensorflow. I am unable to ...
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1answer
569 views

Images Dataset Augmentation with fixed parameters of Crop & Rotation Angle

I have a Data Set of 170 images in total. of each image i want to create 36 images like this. An image is cropped from its top-left corner by cropping 5 percent from the top and from the left side of ...
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1answer
868 views

Data Augmentation in videos

I know some techniques for augmenting data when images are used, but I don't know if there are any such techniques specifically catered to videos. Since videos have an additional temporal dimension ...
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575 views

Why augmenting the training data with binary attributes works better for our dataset?

We have a dataset with multiple features ~400 where all of the features have a histogram as you can see in the following picture (sampled only a few) Our assumption We thought that this looked like ...
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2answers
468 views

Are there libraries or techniques for 'noisifying' text data?

Data augmentation techniques for image data and audio data (eg speech recognition) have proven successful and are now common. Are there libraries or techniques for augmenting text data? For example: ...