Cargando…
A Quantized Convolutional Neural Network Implemented With Memristor for Image Denoising and Recognition
The interference of noise will cause the degradation of image quality, which can have a negative impact on the subsequent image processing and visual effect. Although the existing image denoising algorithms are relatively perfect, their computational efficiency is restricted by the performance of th...
Autores principales: | Zhang, Yuejun, Wu, Zhixin, Liu, Shuzhi, Guo, Zhecheng, Chen, Qilai, Gao, Pingqi, Wang, Pengjun, Liu, Gang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481819/ https://www.ncbi.nlm.nih.gov/pubmed/34602968 http://dx.doi.org/10.3389/fnins.2021.717222 |
Ejemplares similares
-
Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network
por: Chen, Qilai, et al.
Publicado: (2022) -
Organic Memristor with Synaptic Plasticity for Neuromorphic Computing Applications
por: Zeng, Jianmin, et al.
Publicado: (2023) -
Memristor Based Binary Convolutional Neural Network Architecture With Configurable Neurons
por: Huang, Lixing, et al.
Publicado: (2021) -
Improving the Recognition Accuracy of Memristive Neural Networks via Homogenized Analog Type Conductance Quantization
por: Chen, Qilai, et al.
Publicado: (2020) -
Reservoir Computing-Based Design of ZnO Memristor-Type Digital Identification Circuits
por: Wang, Lixun, et al.
Publicado: (2022)