2 papers
cs.LG2022
Distance-Ratio-Based Formulation for Metric Learning
Hyeongji Kim, Pekka Parviainen, Ketil Malde
In metric learning, the goal is to learn an embedding so that data points with the same class are close to each other and data points with different classes are far apart. We propo…
cs.CV2019
Beyond image classification: zooplankton identification with deep vector space embeddings
Ketil Malde, Hyeongji Kim
Zooplankton images, like many other real world data types, have intrinsic properties that make the design of effective classification systems difficult. For instance, the number of…