Questions tagged [siamese-neural-network]

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

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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 ...
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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 ...
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Is there a model for image pair duplicate detection?

Is there a deep learning model for duplicate image pair detection? Looks like I have to use a Siamese network for this. I have a dataset with image pairs with labelling that they are duplicates or not:...
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How to use a Siamese network at test time?

I am trying to understand Siamese networks, and understand how to train them. Once I have a trained network, I want to know if a new image is close or far to other images in the train set, and fail to ...
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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 ...
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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 ...
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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 ...
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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 ...
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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, ...
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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 ...
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