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Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Variants of Triplet networks are robust entities for learning a discrimi...
07/10/2020 ∙ by Milad Sikaroudi, et al. ∙
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Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
We analyze the effect of offline and online triplet mining for colorecta...
07/04/2020 ∙ by Milad Sikaroudi, et al. ∙
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Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
As many algorithms depend on a suitable representation of data, learning...
05/10/2020 ∙ by Milad Sikaroudi, et al. ∙
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Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Siamese neural network is a very powerful architecture for both feature ...
04/05/2020 ∙ by Benyamin Ghojogh, et al. ∙
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Weighted Fisher Discriminant Analysis in the Input and Feature Spaces
Fisher Discriminant Analysis (FDA) is a subspace learning method which m...
04/04/2020 ∙ by Benyamin Ghojogh, et al. ∙
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