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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17 views

Multi-Modal Vs Multi-View learning

What is the difference between Multi-modal & Multi-view in the context of visual data analysis(images) knowing that Multi-view learning deals with Multi descriptors of image.
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21 views

Bag of Tricks: n-grams as additional features?

I've been playing with PyTorch's nn.EmbeddingBag for sentence classification for about a month. I've been doing some feature engineering, playing with different ...
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28 views

Understanding SIFT descriptor calculation

I need to understand how SIFT calculates the descriptors for the keypoints. Intuitively, i understand that it takes each keypoint, calculates the gradients for each pixel in a neighborhood of the ...
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32 views

How is the bias added after the convolution in a CNN?

I'm having trouble understanding how bias is added to the feature extraction convolution. I've seen people either refer to the bias as a single number that changes per filter or the whole matrix that ...
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24 views

(Deep) feature engineering for lambda terms (mathematical expressions, higher order logic formulas) - is such thing?

Automated theorem proving with (deep) reinforcement learning (DRL) approach is hot topic in current AI research when domains of games are becoming saturated and completed research topics. For example, ...
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1answer
160 views

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 ...
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1answer
85 views

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 to get new features that are not actually present in the given set of features. ...
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192 views

What could be a good way to visualise the feature extraction process with MobileNet?

I am trying to create a visualisation for how transfer learning (feature extraction in particular) works with MobileNet. With the ml5.js library, you can extract a ...
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1answer
43 views

Is it a good practice to pad signal before feature extraction?

Is padding, before feature extraction with VGGish, a good practice? Our padding technique is to find the longest signal (which is loaded .wav signal), and then, in ...
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1answer
49 views

How is a ResNet-50 used for deep feature extraction?

I'm trying to implement the vehicle re-identification model described in https://arxiv.org/pdf/2004.06271.pdf. My question focuses on Section 3.2 of the paper, which uses a ResNet-50 for deep feature ...
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13 views

Advice required for identifying bone fragments in CT-scans using STL Files (3D image segmentation)

I am working on a project related to automating the procedure of manually segmenting some bones in CT scans and hopefully if everything goes alright in this stage, move on to do something more with ...
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How to make CNN to recognize whole picture, not just the details?

In my current project I use CNNs to analize plots (CNN autoencoders for feature extraction and KMeans for clusterization) and I get the feeling that these networks, can extract only features that are ...
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1answer
62 views

How can Image Caption work?

I have two models and a file contains captions for images. The output of model 1 is .pkl files that contain the features of the images. Model 2 is the language model that will be trained with the ...
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28 views

Can I use the SIFT feature detector on data other than images?

I know how to use SIFT algorithm for images but I never use it for other kinds of data. I have tabular data (x, y, z, time) where x,y,z is the joint position along x, y, z coordinates. Now, can I ...
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156 views

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 ...
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1answer
124 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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34 views

Graph Neural Networks: Quesitons about different GCN Architectures

This might be moreof a question about nested function classes: For k class node classification in a graph with n nodes, and d feature vector. I want to compare Architecture I: the GCN model of Kipf/ ...
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33 views

How should I use deep learning to find the rotation of an object from its 2D image?

I have 6600 images and I am supposed to know the rotation of the object in each image. So, given an image, I want to regress to a single value. My attempt: I use Resnet-18 to extract a feature vector ...
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61 views

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 ...
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1answer
44 views

Extract Features at Multiple Image-Scales

I try to replicate the results of this paper. They state, that they used VGG16- and VGG19-models pretrained on imagenet and used the output of the last convolutional layer (without relu and max-...
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23 views

What is the best way to do classification using both text and numerical data?

For my BSc thesis I am trying to classify asset price direction (up/down/neutral) using numerical features and Swedish text. The text is short financial news (ca 50 words each) that have sentiment ...
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47 views

Which is more accurate between HRnet-w48 and HigherHRnet-w48 for single person pose estimation?

When I started to look into the deep High-Resolution Net paper, I came to know about the HigherHRNet and the Bottom Up HRNet as well. But I can't find any metrics or proof on which is better for a ...
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15 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
25 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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1answer
63 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
128 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
60 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
1k 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
46 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
163 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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0answers
22 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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19 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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0answers
54 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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1answer
53 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
2k 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
58 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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1answer
415 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
165 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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1answer
71 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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0answers
88 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
108 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
123 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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3answers
117 views

Features Map convolutional neural network [closed]

I have a question about the convolutional neural network. Consider this image: We have a part of an input matrix and a filter. Now, we can do the convolution and the result is a scalar, if it is a ...
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1answer
3k 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 ...