Questions tagged [siamese]

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Siamese networks for comparison of a dataset with multiple features (text, numeric, and ordinal)

Lets assume I have a dataset where each row has ordinal, numerical, and free text columns/features. Some of the rows are grouped together i.e.: ...
• 521
1 vote
23 views

How to use a Siamese network at test time? [closed]

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 ...
• 373
1 vote
52 views

Why does triplet loss outperform contrastive loss?

Trying to learn Siamese networks for ranking tasks from here, I find it hard to understand why triplet loss was ever introduced at all, theoretically. I understand it works better in practice, but ...
• 373
122 views

How to use siamese network in binary classification - inference mode

Siamese network consists of two identical networks. Networks share the same weights. The general workflow is as follows (taken from here): Suppose that I have 10 images of apples, 10 images of ...
• 199
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What is meant by siamese network: train one network for each class or one network for all classes (example of training face recognition)

In siamese networks, the aim is to make closer the data from the same class and push far away the data coming from the different classes. Suppose that we want a face identification system with 5 ...
• 199
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About the calculation of covariance matrix in mahalanobis distance: How $W^TW$ is equal to the covariance matrix? [closed]

I was reading about deep metric learning (from here) and came across the mahalanobis distance. I understood why we can not use euclidean distance if the distribution is not isotropic (the covariance ...
• 199
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Understand the idea of margin in contrastive loss for siamese networks

I was studying siamese networks for authentication. Loss is: Y is 0 for dissimilar pairs and 1 for similar pairs. D_w is the distance (e.g. euclidean distance) between two pairs (by using weights w). ...
• 199
1 vote
11 views

Training in steps has any importance?

I'm trying to train a Siamese network for face Verification and eventually I came across the Contrastive Loss method for embedding vector distancing (kinda... I ...
32 views

How to train a Siamese Net with convolutional + fully connected layers

I am trying to implement a Siamese net for binary classification of audio based on a paper. Below is a summary of the information the authors provided about the model architecture. This model ...
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Validation Loss gets better after adding Augmentation Layers but Test accuracy gets worse

I'm building a Siamese Network which should learn a face comparison function. My model consists a CNN (which gets 2 inputs, and yields 2 embedding vectors). With the outputs I calculate: ...
133 views

How to set up a DL classification model so that it selects from an ever changing menu

The question is edited for clarity after tchainzzz's comments about meta-learning. Let's say we have 10,000 pet pictures and 10,000 kids. Each kid is presented with 10 randomly picked pet pictures at ...
• 185
For a siamese network, contrastive loss is typically used. $$L = y \cdot d(x_0, x_1) + (1-y)\max(0, m - d(x_0, x_1))$$ That is, it tries to reduce the distance for the positive examples and increase ...