5 accepted papers
In large-scale sensor networks, Multivariate Time Series Classification (MTSC) is a pivotal task for identifying events dependent on longitudinal data at the edge. However, existing methods focus on neither the inherent ability of convolutional networks to perceive subsequence features, nor the prol
The olfaction is hardly mentioned in the studies of multi-modal Large Language Models (LLMs). This demo presents a prototypical framework to embody prevalent LLMs with smelling ability using a plug-and-play olfactory signal processing service. To this end, we collect a dataset on Korean beers by sel
Existing Artificial Olfaction (AO) primarily serves two tasks: Odor Classification (OC) and Odor Source Localization (OSL). Both tasks w.r.t. indoor event detection scenarios are studied either using a single electronic nose (e-nose) mounted on the ceiling or mobile robot(s) equipped with e-noses. H
Category-specific models are provenly valuable methods in 3D single object tracking (SOT) regardless of Siamese or motion-centric paradigms. However, such over-specialized model designs incur redundant parameters, thus limiting the broader applicability of 3D SOT task. This paper first introduces un…
The explosive popularity of smart manufacturing has caught the attention of researchers in terms of intelligent mold processing and management. Machining mold components is a crucial step in the mold production process for many industries, which creates (e.g., cutting, drilling, and shaping a metal)…