In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...
Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...
A new technical paper titled “Enabling Physical AI at the Edge: Hardware-Accelerated Recovery of System Dynamics” was ...
Abstract: The morphological undecimated wavelet (MUW) is an efficient feature extraction algorithm for bearing fault diagnosis. Currently, the researched MUW is mainly focused on background noise ...
Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...
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