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.

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9 views

Cocatenate feature extractor layers with different channels

I have a network architecture for feature extraction and I wanted to concatenate layers of the same dimensions but with different feature channels. ...
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13 views

Neural Network for locating shifting resonant frequencies

I have multiple FFT's taken from a sample at different pressures, through different analysis I can see that the resonant frequencies are shifting in the spectrum for each FFT at a different pressure. ...
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1answer
22 views

Which type of feature extractor do you suggest to classify sensor data?

I have IMU (Inertial Measurment Unit- 6 axis) sensor data. The sensor attached on a car and 7 different drivers wipe on same path. I want to extract features and classify drivers. Which type of ...
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29 views

Can I use the full dataset for training the CNN feature extractor?

I built a CNN model for extracting features from its dense layer. The extracted features are then used for classification using KNN and Random Forest classifier. My question is, can I use the whole ...
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20 views

Unix timestamps for Recurrent Neural Networks

I want to use RNN for classifying whole sequences of events, generated by website visitors. Each event has some categorical properties and a Unix timestamp: ...
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2answers
111 views

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 ...
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1answer
49 views

What are some good papers or resources for aspect extraction and opinion modelling from video or audio?

I am quite new to deep learning. I just finished the deep learning specialization by Professor Andrew NG and Deep Learning AI. Now, my professor (instructor) has advised me to look into some classic ...
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1answer
104 views

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?
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1answer
39 views

Corner detection algorithm gives very high value for slanted edges?

I have tried implementing a basic version of shi-tomasi corner detection algorithm. The algorithm works fine for corners but I came across a strange issue that the algorithm also gives high values for ...
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1answer
59 views

How to choose a suitable threshold value for shi-tomasi corner detection algorithm?

While implementing shi-tomasi corner detection algorithm i got stuck at deciding a suitable threshold for corner detection. In shi-tomasi algorithm all those points that qualify ...
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20 views

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 ...
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18 views

How can I extract images features in k-few shot learning to do semantic segmentation?

I've just started to learn N-way k-few shot learning, and I have understood how to use, i.e., Prototypical networks or Siamese networks to classify images. But, if I want to use those networks to do ...
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18 views

Feature extraction for exponentially damped signals

I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features ...
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50 views

What are examples of commonly used feature and readout maps?

It is well-known that deep feedforward networks can approximate any continuous function from $\mathbb{R}^k$ to $\mathbb{R}^l$, (uniformly on compacts). However, in practice feature maps are ...
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29 views

PCA + LDA feature extraction

I am trying to reduce the size of my features vectors using PCA and LDA. Following the approach presented here, I cannot understand step 3 and step 4 described in that approach. Why is the ...
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1answer
41 views

Extract product information from email receipt HTML

I am trying to extract product information from email receipts HTML. Most services I have found focus on OCR from paper receipts or PDFs. I would imagine that extraction of product information would ...
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2answers
755 views

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 ...
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0answers
42 views

Plot class activation heatmap of Caffe Model in Python

Given the following 3 research papers, the authors have shown different heatmap graphical representations for features of the trained CNN models: On the performance of Convnet feature for place ...
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25 views

What are the frameworks for automated feature engineering?

I want to ask you what are the frameworks or scientific papers that deal with automated feature extraction/engineering (not based on domain knowledge)? What I mean by feature extraction or ...
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1answer
198 views

What are the features get from a feature extraction using a CNN?

I've just started to learn CNN and somewhere I have read if I remove the last FCL I will get the features extracted from the input image but... what are those features? Are they numbers? Labels? An ...
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1answer
92 views

How can I use feature extraction in CNN with image segmentation?

I'm just started to learn about meta learning and CNN and in most paper that I've read they mention to have one CNN to feature extraction. These features will help the another network. I don't know ...
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16 views

CBIR Evaluation on contextually different data

How good would a CBIR system trained on a dataset, for example, DELF, trained on the Google Landmarks dataset, perform when evaluated on a contextually different dataset such as the WANG or the COREL ...
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33 views

Extracting Descriptors and feature points for 3d mesh

I'm programming my work with python, and I have a mesh and I want to extract 3d descriptors and feature points from it( trying to work on multi-scale strategy) , to visualize them later on the mesh, ...
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18 views

Learning Features from a Pre-trained Network

I am currently working on learning the features provided by a pre-trained network for image retrieval. Currently I take the features provided by the pre-trained network, use global max pooling to ...
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81 views

Can we use Autoencoders for unsupervised CNN feature learning?

I searched through the internet but couldn't find a reliable article that answers this question. Can we use Autoencoders for unsupervised CNN feature learning of unlabeled images like the below and ...
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1answer
82 views

Key Point Extraction the best method?

I have been researching about determining some key points on an image, in this case I'm gonna use cloth (top side of human body) pictures. I want to detect some corner points on those. Example: I ...
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3answers
109 views

How do I determine which relevant features have been learned during training in a CNN?

Is there any way to control the extraction of features? How do I determine which features are been learned during training, i.e relevant information is been learned or not?
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1answer
1k views

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 ...