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Found 5 papers, 1 papers with code
Within-basket Recommendation via Neural Pattern Associator
Within-basket recommendation (WBR) refers to the task of recommending items to the end of completing a non-empty shopping basket during a shopping session.
Adaptive additive classification-based loss for deep metric learning
Also recently, classification loss and proxy-based metric learning have been observed to lead to faster convergence as well as better retrieval results, all the while without requiring complex and costly sampling strategies.
Calibrated neighborhood aware confidence measure for deep metric learning
Deep metric learning has gained promising improvement in recent years following the success of deep learning.
Ranked #3 on
Metric Learning
on CARS196
Unbiased Evaluation of Deep Metric Learning Algorithms
Deep metric learning (DML) is a popular approach for images retrieval, solving verification (same or not) problems and addressing open set classification.
Scalable Logo Recognition using Proxies
Logo recognition is a challenging problem as there is no clear definition of a logo and there are huge variations of logos, brands and re-training to cover every variation is impractical.
