Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [feature-extraction]

For questions related to the concept of feature extraction, which is a set of techniques used to derive or create features from the existing set of features. Feature extraction is different from feature selection, which is used to select a subset of the existing features.

For more details, see e.g. https://en.wikipedia.org/wiki/Feature_extraction.

59 questions
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Is word embedding a form of feature extraction?

Feature extraction is a concept concerning the translation of raw data into the inputs that a particular machine learning algorithm requires. These derived features from the raw data that are actually relevant to tackle the underlying problem. On…
HiDDeN
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Are deep learning models suitable for training with sparse data?

I am training a generative adversarial network (GAN) to generate images given edge histogram descriptor (EHD) features of the image. The EHD features are themselves sparse (meaning they contain a lot of zeroes). While training the generator loss and…
varsh
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Where do the feature extraction and representation learning differ?

Feature selection is a process of selecting a subset of features that contribute the most. Feature extraction allows getting new features that are not actually present in the given set of features. Representation learning is the process of learning…
hanugm
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When is it necessary to manually extract features to feed into the neural network rather than providing raw data?

Usually, Neural Networks uses raw data. You do not need to extract features manually. NN's can find & extract good features which is a pattern of an image, signal or any kind of data. When we check layer outputs in a NN, we can see and visualize how…
dasmehdix
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What are bag-of-features in computer vision?

In computer vision, what are bag-of-features (also known as bag-of-visual-words)? How do they work? What can they be used for? How are they related to the bag-of-words model in NLP?
nbro
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Is it true that untrained CNNs can be used as feature extractors?

I've heard somewhere that due to their nature of capturing spatial relations, even untrained CNNs can be used as feature extractors? Is this true? Does anyone have any sources regarding this I can look at?
Alex
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Is such a captcha AI-resistant?

Let's say we have a captcha system that consists of a greyscale picture (of a part of a street or something akin to re-captcha), divided into 9 blocks, with 2 missing pieces. You need to choose the appropriate missing pieces from over 15…
user38359
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How translation invariance is achieved in CNNs?

I am trying to understand how translation invariance is achieved in CNNs. For example, consider the following simple binary classification problem: predicting whether the letter that appears on an image is A or B. We want our network to be…
ado sar
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Order of features learned by DNNs during training?

I'm looking for papers probing into the question of what features get learned when (or equivalently what subproblems get "solved" when) during the training process. For example, a paper showing that a Convnet trained on MNIST learns to distinguish 0…
jon_simon
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How to calculate a meaningful distance between multidimensional tensors

TLDR: given two tensors $t_1$ and $t_2$, both with shape $(c,h,w),$ how shall the distance between them be measured? More Info: I'm working on a project in which I'm trying to distinguish between an anomalous sample (specifically from MNIST) and a…
Hadar Sharvit
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How to convert color information to 1D feature vector?

We are making a classification model that takes a clip of a movie as an input and predicts who the director is. Roughly speaking, it will be a model that understands film directors' unique style. We are going to extract 5 features from a movie: a…
Katsuragi Misato
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What is the difference between feature extraction and fine-tuning in transfer learning?

I'm building a model for facial expression recognition, and I want to use transfer learning. From what I understand, there are different steps to do it. The first is the feature extraction and the second is fine-tuning. I want to understand more…
Speedskillsx
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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: Running the convolutional base over your dataset,…
CechMS
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Statistical method for selecting features for classification

I'm working on a classifier for the famous MNIST handwritten data set. I want to create a few features on my own, and I want to be able to estimate which feature might perform better before actually training the classifier. Lets say that I create…
IsolatedSushi
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Visualisation for Features to Predict Timeseries Data

I have a course assignment to use an LSTM to predict the movement directions of stock prices. One of the things I am asked to do is provide a visualization to compare the predictive powers of a set of N features (e.g. 1-day return, volatility,…
georgi koyrushki
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