Questions tagged [feature-learning]

For questions related to feature learning (also known as representation learning), which is a set of techniques that can learn the features associated with the raw data. It is similar to feature engineering, but, in the case of feature learning, the features are learned and not handcrafted.

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56
votes
3answers
50k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
5
votes
2answers
73 views

What are examples of approaches to dimensionality reduction of feature vectors?

Given a pre-trained CNN model, I extract feature vector of images in reference and query dataset with several thousands of elements. I would like to apply some augmentation techniques to reduce the ...
4
votes
2answers
441 views

How to understand the concept of self-supervised learning in AI?

I am new to self-supervised learning and it all seems a little magical at the moment. The only way I can get an intuitive understanding is to assume that, for real-world problems, features are still ...
4
votes
2answers
3k views

What is feature embedding in the context of convolutional neural networks?

What are feature embeddings in the context of convolutional neural networks? Is it related to bottleneck features or feature vectors?
3
votes
1answer
46 views

Why different images of the same person, under some restrictions, are in a 50 dimension manifold?

In this lecture (starting from 1:31:00) the professor says that the set of all images of a person lives in a low dimensional surface (compared the the set of all possible images). And he says that the ...
2
votes
1answer
52 views

Can a neural network learn to predict a number given a binarized image of a rectangle?

Let's assume that we have a regression problem. Our input is just binarized image that contains a single rectangle and we want to predict just a float number. Actually, this floating-point number ...
2
votes
2answers
55 views

How do we know that the neurons of an artificial neural network start by learning small features?

I'd like to ask you how do we know that neural networks start by learning small, basic features or "parts" of the data and then use them to build up more complex features as we go through ...
2
votes
0answers
25 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/ ...
2
votes
1answer
29 views

What does “class-level discriminative feature representation” mean in the paper “Semi-Supervised Deep Learning with Memory”?

I am reading the paper Semi-Supervised Deep Learning with Memory (2018) by Yanbei Chen et al. The topic is the classification of images using semi-supervised learning. The authors use a term on page ...
1
vote
1answer
79 views

When should I use feature learning as opposed to feature engineering?

With the advancement of deep learning and a few others automated features learning techniques, manual feature engineering started becoming obsolete. Any suggestion on when to use manual feature ...
1
vote
1answer
308 views

How to generate labels for self-supervised training?

I've been reading a lot lately about self-supervised learning and I didn't understand very well how to generate the desired label for a given image. Let's say that I have an image classification task, ...
1
vote
0answers
47 views

Extending patch based image classification into image classification

I am trying to classify tampered, pristine images from set of images, in that I have built a network in which I would divide the image into multiple overlapping patches and then classify them into ...
1
vote
1answer
105 views

Does self-supervised learning require auxiliary tasks?

Self-supervised learning algorithms provide labels automatically. But, it is not clear what else is required for an algorithm to fall under the category "self-supervised": Some say, self-...
1
vote
0answers
16 views

Convolutional Feature Encoding Methods in DCNN

In Computer Vision, feature encoding methods are used on pre-trained DCNN to increase the feature robustness to certain conditions such as viewpoint/appearance variations ref. I was just wondering if ...
1
vote
0answers
48 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 ...
1
vote
0answers
36 views

Is it possible to use adversarial training to learn invariant features?

Given a set of time series data that are generated from different sites where all sites are investigating the same objective but with slightly different protocols. Is it possible to use adversarial ...
0
votes
1answer
40 views

classification of unseen classes of image in open set classification

I have a scanned image, and they need to be classified in one of the pre-defined image classes, so that it can be sorted. However, the problem is the open nature of the classes. At testing time, new ...