Abstract: The accurate prediction of gas mixture concentrations plays a vital role in the development of intelligent electronic nose. However, in most previous studies, time-series data from sensor ...
Abstract: The growth of interconnected devices has led to an enormous volume of temporal data that requires specialized compression models for efficient storage. Besides this, most applications need ...
We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...
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