3
votes
How to combine different models in Keras?
You can get the output of your models with model.output or get_layer
and combine them with ...
- 350
2
votes
Difference between Siamese Network and Prototypical Networks for One Shot Learning
For unseen classes at inference time, one-shot learning is quite similar when using Siamese networks and prototypical networks. Both approaches involve using your trained network to generate
an ...
- 131
2
votes
Accepted
Siamese model accuracy stuck at 0.5
Turns out the problem was hidden in the loss function. I decided to change it from Contrasive Loss to Categorical Crossentropy just for fun, and with some kind of "magic" it worked.
from:
<...
- 31
1
vote
Accepted
Siamese Network for face comparison wont learn, accuracy stuck on 0.5, and loss stuck too
I had many small implementation problems, mostly on the data generation side. 2 main problems which I remember made a big change:
I have changed "steps_per_epoch" to some big number and ...
- 111
1
vote
How gradients are flown back to Network in siamese architecture? How weights of all CNN models are same even when using different models
You do three forward passes for the three inputs and calculate one loss. So some modules (maybe all) are used three times. As the gradients depend on the inputs, three gradients get calculated and ...
- 111
1
vote
How gradients are flown back to Network in siamese architecture? How weights of all CNN models are same even when using different models
You only create ONE model for a siamese network that you pass your inputs to.
(You have created three models in the example)
So in your triplet case you would pass the three inputs seperatly to the ...
- 193
1
vote
Sneakers representation learning
Best is to start from pre-trained encoding. Please check TFHub (https://tfhub.dev/google/collections/image/1).
I have worked myself with encoding of shoes for a sport fashion companies. Remember that ...
- 341
1
vote
Why does Siamese neural networks use tied weights and how do they work?
You could have a single network, feed both inputs separately, compute the distance/loss, then perform backpropagation.
Or
(as in the cited paper) you could initialize a network, and then create a ...
- 36
1
vote
Siamese Network in Keras
From Official Keras examples:
Image similarity estimation using a Siamese Network with a triplet loss
Training a Siamese Network to compare the similarity of images using a triplet loss function.
A ...
- 4,018
1
vote
Siamese Network in Keras
Thats perfect I am searching implementation too, and I found these resources.
Here pyimagesearch website https://www.pyimagesearch.com/2020/11/23/building-image-pairs-for-siamese-networks-with-python/
...
- 11
1
vote
Accepted
Training a Siamese Neural Network for object similarity assessment
without going into architecture that looks reasonable but always can be updated: Weights are dominantly updated for the negative pairs. why?
In the train set where you have (approx) 10 000 times more ...
- 5,739
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