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Circle loss: A unified perspective of pair similarity optimization
This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming
to maximize the within-class similarity s_p and minimize the between-class similarity s_n …
to maximize the within-class similarity s_p and minimize the between-class similarity s_n …
Racial bias within face recognition: A survey
S Yucer, F Tektas, N Al Moubayed… - ACM Computing Surveys, 2024 - dl.acm.org
Facial recognition is one of the most academically studied and industrially developed areas
within computer vision where we readily find associated applications deployed globally. This …
within computer vision where we readily find associated applications deployed globally. This …
Exploring racial bias within face recognition via per-subject adversarially-enabled data augmentation
Whilst face recognition applications are becoming increasingly prevalent within our daily
lives, leading approaches in the field still suffer from performance bias to the detriment of …
lives, leading approaches in the field still suffer from performance bias to the detriment of …
Surveying racial bias in facial recognition: Balancing datasets and algorithmic enhancements
Facial recognition systems frequently exhibit high accuracies when evaluated on standard
test datasets. However, their performance tends to degrade significantly when confronted …
test datasets. However, their performance tends to degrade significantly when confronted …
Deep speaker embeddings for far-field speaker recognition on short utterances
Speaker recognition systems based on deep speaker embeddings have achieved
significant performance in controlled conditions according to the results obtained for early …
significant performance in controlled conditions according to the results obtained for early …
Rotation consistent margin loss for efficient low-bit face recognition
In this paper, we consider the low-bit quantization problem of face recognition (FR) under
the open-set protocol. Different from well explored low-bit quantization on closed-set image …
the open-set protocol. Different from well explored low-bit quantization on closed-set image …
A bayesian framework for integrated deep metric learning and tracking of vulnerable road users using automotive radars
With the recent advancements in radar systems, radar sensors offer a promising and
effective perception of the surrounding. This includes target detection, classification and …
effective perception of the surrounding. This includes target detection, classification and …