Search Results for author:
Found 3 papers, 1 papers with code
Merging Vision Transformers from Different Tasks and Domains
This work targets to merge various Vision Transformers (ViTs) trained on different tasks (i. e., datasets with different object categories) or domains (i. e., datasets with the same categories but different environments) into one unified model, yielding still good performance on each task or domain.
Uncovering multifunctional mechano-intelligence in and through phononic metastructures harnessing physical reservoir computing
The recent advances in autonomous systems have prompted a strong demand for the next generation of adaptive structures and materials to possess more built-in intelligence in their mechanical domain, the so-called mechano-intelligence (MI).
Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data
In this paper, we demonstrate that unsupervised learning algorithms perform competitively with supervised algorithms for detecting MAs on EDA data collected in both a lab-based setting and a real-world setting comprising about 23 hours of data.
