Cargando…
A Low-Power Hardware Architecture for Real-Time CNN Computing
Convolutional neural network (CNN) is widely deployed on edge devices, performing tasks such as objective detection, image recognition and acoustic recognition. However, the limited resources and strict power constraints of edge devices pose a great challenge to applying the computationally intensiv...
Autores principales: | Liu, Xinyu, Cao, Chenhong, Duan, Shengyu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965634/ https://www.ncbi.nlm.nih.gov/pubmed/36850642 http://dx.doi.org/10.3390/s23042045 |
Ejemplares similares
-
Hardware-Efficient Stochastic Binary CNN Architectures for Near-Sensor Computing
por: Parmar, Vivek, et al.
Publicado: (2022) -
CNN Hardware Accelerator for Real-Time Bearing Fault Diagnosis
por: Chung, Ching-Che, et al.
Publicado: (2023) -
HFNet: A CNN Architecture Co-designed for Neuromorphic Hardware With a Crossbar Array of Synapses
por: Gopalakrishnan, Roshan, et al.
Publicado: (2020) -
Introduction to computer systems architecture-hardware
por: Sumner, F H
Publicado: (1974) -
Real-Time Sound Source Localization for Low-Power IoT Devices Based on Multi-Stream CNN
por: Ko, Jungbeom, et al.
Publicado: (2022)