Nov 16, 2020 · We estimate the similarities between objects through a kernel-based t-student distribution to measure the markers' distance and the new data ...
Nov 9, 2022 · We present evidence that our proposal can represent complex spaces, for instance, when groups of similar objects are located in disjoint regions ...
Nov 20, 2020 · We propose a novel deep metric learning method. Differently from many works on this area, we defined a novel latent space obtained through ...
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Nov 18, 2020 · We present evidences that our proposal can represent complex spaces, for instance, when groups similar objects are located in disjoint regions.
Nov 9, 2022 · We propose a novel deep metric learning method. Differently from many works in this area, we define a novel latent space obtained through an ...
Our method learns a set of hierarchical non- linear transformations by transferring discriminative knowl- edge from the labeled source domain to the unlabeled ...
Quaterion is a framework for fine-tuning similarity learning models. The framework closes the "last mile" problem in training models for semantic search, ...
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Nov 30, 2023 · Similarity-based retrieval involves automatically analyzing a music track and fetching analogous tracks from a database. Auto-tagging, on the ...
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
... Region similarity learning provides a way to transfer knowledge from known regions to new (or unknown) regions, which can facilitate applications such as ...