Generalized out-of-distribution detection: A survey
Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …
machine learning systems. For instance, in autonomous driving, we would like the driving …
Adversarial attacks on foundational vision models
N Inkawhich, G McDonald, R Luley - ar** large, pretrained, task-agnostic foundational
vision models such as CLIP, ALIGN, DINOv2, etc. In fact, we are approaching the point …
vision models such as CLIP, ALIGN, DINOv2, etc. In fact, we are approaching the point …
[HTML][HTML] Hierarchical-taxonomy-aware and attentional convolutional neural networks for acoustic identification of bird species: A phylogenetic perspective
The study of bird populations is crucial for biodiversity research and conservation. Deep
artificial neural networks have revolutionized bird acoustic recognition; however, most …
artificial neural networks have revolutionized bird acoustic recognition; however, most …
Collaborative Knowledge Distillation via a Learning-by-Education Node Community
A novel Learning-by-Education Node Community framework (LENC) for Collaborative
Knowledge Distillation (CKD) is presented, which facilitates continual collective learning …
Knowledge Distillation (CKD) is presented, which facilitates continual collective learning …
Athena–The NSF AI Institute for Edge Computing
Abstract The National Science Foundation (NSF) Artificial Intelligence (AI) Institute for Edge
Computing Leveraging Next Generation Networks (Athena) seeks to foment a transformation …
Computing Leveraging Next Generation Networks (Athena) seeks to foment a transformation …
Detecting unregistered users through semi-supervised anomaly detection with similarity datasets
Recent research has focused on exploring systems that incorporate anomaly detection
models to automate the addition of users in user recognition systems. Anomaly detection, a …
models to automate the addition of users in user recognition systems. Anomaly detection, a …
From Adversaries to Anomalies: Addressing Real-World Vulnerabilities of Deep Learning-based Vision Models
MJ Inkawhich - 2024 - search.proquest.com
Abstract Deep Neural Networks (DNNs) have driven the performance of computer vision to
new heights, which has led to them to being rapidly integrated into many of our real-world …
new heights, which has led to them to being rapidly integrated into many of our real-world …