4 papers
Dual-Domain Masked Image Modeling: A Self-Supervised Pretraining Strategy Using Spatial and Frequency Domain Masking for Hyperspectral Data
Shaheer Mohamed, Tharindu Fernando, Sridha Sridharan +2
Hyperspectral images (HSIs) capture rich spectral signatures that reveal vital material properties, offering broad applicability across various domains. However, the scarcity of la…
Spectral-Enhanced Transformers: Leveraging Large-Scale Pretrained Models for Hyperspectral Object Tracking
Shaheer Mohamed, Tharindu Fernando, Sridha Sridharan +2
Hyperspectral object tracking using snapshot mosaic cameras is emerging as it provides enhanced spectral information alongside spatial data, contributing to a more comprehensive un…
Inductive Graph Few-shot Class Incremental Learning
Yayong Li, Peyman Moghadam, Can Peng +2
Node classification with Graph Neural Networks (GNN) under a fixed set of labels is well known in contrast to Graph Few-Shot Class Incremental Learning (GFSCIL), which involves lea…
Object Registration in Neural Fields
David Hall, Stephen Hausler, Sutharsan Mahendren +1
Neural fields provide a continuous scene representation of 3D geometry and appearance in a way which has great promise for robotics applications. One functionality that unlocks uni…