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Large coordinate kernel attention network for lightweight image super-resolution
However, existing lightweight super-resolution (SR) methods seldom pay attention to designing efficient building block with multi-scale receptive field for local modeling, and their LKA modules face a quadratic increase in computational and memory footprints as the convolutional kernel size increases.
DOCTOR: Dynamic On-Chip Remediation Against Temporally-Drifting Thermal Variations Toward Self-Corrected Photonic Tensor Accelerators
While off-chip noise-aware training and on-chip training have been proposed to enhance the variation tolerance of optical neural accelerators with moderate, static noises, we observe a notable performance degradation over time due to temporally drifting variations, which requires a real-time, in-situ calibration mechanism.
A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Neuronal morphology is essential for studying brain functioning and understanding neurodegenerative disorders.
