Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation.

Advances in end-to-end rPPG approaches have focused on this transformation where attention mechanisms are crucial for feature extraction.

This makes it easily extensible and much more expressive than existing toolkits. It supports all 9 and all 10 of the decision-based group metrics of two popular review articles.

Video Anomaly Detection (V AD) finds widespread applications in security surveillance, traffic monitoring, industrial monitoring, and healthcare.

Figure 1: (a) Classification space of two graph tasks when no task ID is provided.

We present a novel approach for test-time adaptation via online self-training, consisting of two components.

While neural networks can enjoy an outstanding flexibility and exhibit unprecedented performance, the mechanism behind their behavior is still not well-understood.

Evidential Deep Learning (EDL), grounded in Evidence Theory and Subjective Logic (SL), provides a robust framework to estimate uncertainty for out-of-distribution (OOD) detection alongside traditional classification probabilities.