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Questions tagged [siamese-neural-network]

Use for questions on A Siamese neural networks, sometimes called twin neural networks.

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Calculating class-specific permutation feature importances for multilabel classification problem

I would like to apply the permutation feature importance technique to rank the features of a siamese network model that I trained. I am currently using this siamese network to perform some kind of ...
ashenflower's user avatar
1 vote
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Is it possible to have a good validation accuracy with random labels?

I'm currently trying to train a siamese network to determine if two inputs are similar or not. The inputs are power consumption traces and I'm basically using the siamese network as some sort of ...
WINTERSDORFF Raphael's user avatar
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RAM usage increases linearly while training. What could be causing the issue?

I'm training a siamese neural network with semi-hard batching, RAM usage increases linearly over epochs, peaking at 60GB, then switches from GPU to CPU, slowing down training. I'm using Windows with ...
Ahmed Altunkaya's user avatar
9 votes
1 answer

What is the difference between the triplet loss and the contrastive loss?

What is the difference between the triplet loss and the contrastive loss? They look same to me. I don't understand the nuances between the two. I have the following queries: When to use what? What ...
Exploring's user avatar
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Is there a state-of-the-art deep learning paper that uses center point regression instead of bounding box regression, for object tracking?

Almost all deep learning based object tracking methods perform bounding box regression. Siamese-based networks which are very popular for object tracking also perform bounding box regression most of ...
Code Of Duty's user avatar
3 votes
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Why are Siamese Neural Networks used instead of a single neural network?

Siamese Neural Networks are a type of neural network used to compare two instances and infer if they belong to the same object. They are composed by two parallel identical neural networks, whose ...
IgnacioGaBo's user avatar
1 vote
1 answer

How contrastive loss work intuitively in siamese network

I am having issue in getting clear concept of contrastive loss used in siamese network. Here is pytorch formula ...
Talha Anwar's user avatar
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How can Siamese Neural Networks accept a variable number of inputs?

Traditionally, Siamese Neural Networks have two inputs. With some tweaking, you can get them to accept any number of inputs. What I don't understand is how to get them to accept variable numbers of ...
GameDungeon's user avatar
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Why is my siamese network learning very well in e.g. 1 out of every 5 runs?

Why is my siamese network learning very well in e.g. 1 out of every 5 runs? The rest of the time it's not learning and maintains an accuracy of 0.5. Any explanations? Is the contrastive loss taken in ...
Ari K's user avatar
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How do gradients are flown back into the Siamese network when branching is done?

I am curious about the working of a Siamese network. So, let us suppose I am using a triplet loss for my network and I have instantiated single CNN 3 times and there are 3 inputs to the network. So, ...
Deshwal's user avatar
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On learning to rank tasks. Could it be that the input of the Siamese network is a vector, or should it be exclusively raw text?

I'm developing a method to document and query representation as concept vectors (bag-of-concepts). I want to train a machine learning model on ranking (learning to rank a task). So I have document ...
mike sam's user avatar