Linked Questions

27 votes
4 answers
17k views

Is it a good idea to use CNN to classify 1D signal?

I am working on the sleep stage classification. I read some research articles about this topic many of them used SVM or ensemble method. Is it a good idea to use convolutional neural network to ...
Fazla Rabbi Mashrur's user avatar
20 votes
3 answers
27k views

MNIST digit recognition: what is the best we can get with a fully connected NN only? (no CNN)

To fully understand how it works internally, I'm re-writing a neural network from scratch in Python + numpy only. (As it's for learning purposes, performance is not an issue). Before moving to ...
Basj's user avatar
  • 632
2 votes
2 answers
2k views

Use matrix feature for machine learning or cluster analysis

I have a bunch of features that I would like to use for classification/machine learning and cluster analysis. Normally I use single point values or transformations of values for features and ...
AbeeCrombie's user avatar
2 votes
2 answers
709 views

How do filters affect the training loss in a convolutional neural network?

I am training a model, I am trying to lower the training loss. While testing different architectures I increased the number of filters to 128 from 64 - this reduced the training loss. I do not ...
Tino Uchiha's user avatar
0 votes
2 answers
1k views

Weight's shape of Convolution Neural Network?

I've have read that cnn have neuron per pixel but also read that it is not true. so what is the actual answer? and what I know is cnn tries to adjust the weight matrix which is also a kernel matrix, i ...
Nervous Hero's user avatar
4 votes
1 answer
2k views

How to count the parameters in a convolution layer?

I'm preparing for an exam in Computer Vision. I came across with the following question from one of the exams: What is the number of parameters of a convolution layer in a neural network, when the ...
vesii's user avatar
  • 221
2 votes
1 answer
617 views

What is a convolutional neural network

I have been studying neural networks and I recently found out about deep learning and convolutional neural networks. Can someone give me a newbie introduction to convolutional neural networks, what ...
jjepsuomi's user avatar
  • 5,847
1 vote
1 answer
273 views

Can we express CNNs in terms of a MLP?

I have been wondering whether a convolution can be represented in terms of an MLP. We can say that in convolution we have shared parameters between different neurons. But how to express this ...
Nomaan Qureshi's user avatar
0 votes
0 answers
122 views

Clarifying terminology of concepts in a CNN

Despite having dealt with Machine Learning for a few years now, I still find myself sporadically confused with elementary terminology, especially when it comes to Convolutional Neural Networks, and I'...
silver's user avatar
  • 101
-1 votes
1 answer
79 views

Machine learning and Artificial intelligence algorithms in identifying and classifying Airplane parts

Airplane parts and functions Can Machine Learning and Artificial intelligence Algorithms assist in identifying and classifying Airplane images parts?
Prashant Akerkar's user avatar
0 votes
0 answers
84 views

How can I mathematically explain the convolutional neural network?

How can I give notations to the whole CNN network? Like, if I feed input 'x' to feature extractor, we will get the extracted feature embedding vector at the end that will be passed to the linear ...
Tariq Hussain's user avatar
1 vote
1 answer
77 views

Implementation of a convolution layer in a cnn

This questions deals with the implementation of a convolution layer. First I like to make clear what I understand about cnn's. A cnn uses filters/kernels to find geometrical features from the input ...
Th0rn's user avatar
  • 11
1 vote
1 answer
74 views

What is the “web” drawing for a graph neural network?

It is common to draw a neural network as a "web" of neurons and connections, such as the "web" below of a multilayer perception that has input neurons in white, hidden neurons in ...
Dave's user avatar
  • 64.7k
1 vote
1 answer
73 views

"Milder" than a convolutional neural network: not forcing connections to be perfectly equal or exactly zero, but penalizing such behavior

Convolutional neural networks (CNNs) do regularization (of sorts) by forcing some weights to be dropped and others to be zero. Borrowing some drawings from another post of mine... Apply the filter to ...
Dave's user avatar
  • 64.7k
0 votes
0 answers
65 views

How can a cnn-lstm learn time-related aspects when these are gone by using a cnn in the first layers?

I recently learned about cnn-lstm architectures for time series, where the cnn part of the architecture acts as a feature-extractor. However, I struggle to grasp why there is still a 'time-related' ...
intStdu's user avatar
  • 101

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