Dec 10, 2021 · We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection.

We propose Hyperdimensional Feature Fusion (HDFF), a novel OOD detection method that applies the HDC concepts of Encoding and Bundling to the features from ...

This work uses similarity-preserving semi-orthogonal projection matrices to project the feature maps from multiple layers into a common vector space and ...

OOD detection, where OOD samples are distinguished from in-distribution (ID) samples, is thus an important task. OOD detection has been addressed widely in ...

Hyperdimensional Feature Fusion (HDFF) is a post-hoc addition to a pretrained network that fuses multi-scale features from the network in a hyperdimensional ...

Hyperdimensional Feature Fusion for Out-of-Distribution Detection: ... In order to apply our hyperdimensional feature fusion to the feature maps of a DNN ...

We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection.

May 9, 2024 · We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection. In contrast to ...

Dec 10, 2021 · We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection.

We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection. Out-of-Distribution Detection ...