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model = SVC(kernel='linear', probability=True)
I am looking forword for triple loss method for real-time-deep-face-recognition
after checking "Make_classifier_git.py", understand u using svm to pre…
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facenet use triplet-loss to train net,minimizes the distance between anchor and a positive,maximizes the distance between anchor and a negative of a different identity.
while the network is training,…
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Hello,I would like to know that if there is anyone working actively on the improvement of this tracker?
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Dear authors,
I was trying to reproduce repllama/repmistral and to understand the logic of the code.
# 1. Why use cross-entropy loss in contrastive learning?
in this file `/usa/dayu/Tab…
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Hi @filipradenovic ,
For your experiment on networks with whitening learned end-to-end, with triplet loss, trained on the Google Landmarks dataset 2018: could you share to which value the GeM pooli…
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The title is self explanatory! Could you share also the notebook you have used to calibrate the fbank_net ?
It seems (as per your notes it performs better)
Thanks
pb
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https://arxiv.org/abs/1612.03900
https://pdfs.semanticscholar.org/9a0c/8fbc6f4f48f736e0f25006c3a9d8c7da83e5.pdf
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## T5-Generation Fine-tuning Task
### Data Preparation
- can only use specially-preprocessed: speaker-spec dataset, because the max input length for t5 is 512.
- preprocessing
1. `lib/create…
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Hello, you can introduce this data? i meet data like this {a, b, c}，each element is article.
now, it tells me this a and b's similarity greater than a and c.(distance(a, b) > distance(a, c)), i kn…
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Hello,
I'm successfully using your tripletlosslayer.py to train a triplet net, but I have some doubts:
- The self.margin parameter is only used in the forward() function to compute the loss, but n…