A structurally regularized cnn architecture via adaptive subband decomposition
We propose a generalized convolutional neural network (CNN) architecture that first
decomposes the input signal into subbands by an adaptive filter bank structure, and then …
decomposes the input signal into subbands by an adaptive filter bank structure, and then …
Optimization of Scatter Network Architectures and Bank Allocations for Sparse CNN Accelerators
Sparse convolutional neural network (SCNN) accelerators eliminate unnecessary
computations and memory access by exploiting zero-valued activation pixels and filter …
computations and memory access by exploiting zero-valued activation pixels and filter …
Properties and applications of a structurally regularized CNN architecture via adaptive subband decomposition
P Sinha - 2024 - escholarship.mcgill.ca
Dans cette thèse, nous présentons le concept d'architecture CNN de décomposition en sous-
bandes qui peut apprendre les coefficients de décomposition en sous-bandes à partir d'un …
bandes qui peut apprendre les coefficients de décomposition en sous-bandes à partir d'un …
Design and verification of convolutional neural network accelerator
G Xiang, J Sui, X Zhang - International Conference on Signal …, 2023 - spiedigitallibrary.org
The existing software implementation schemes of Convolutional Neural Networks (CNN)
cannot meet the requirements of computing performance and power consumption. To further …
cannot meet the requirements of computing performance and power consumption. To further …