Lightweight error-tolerant edge detection using memristor-enabled stochastic computing
Abstract The demand for efficient edge computer vision has spurred the development of stochastic computing for image processing. Memristors, by introducing their inherent switching stochasticity into computation, readily enable stochastic image processing. Here, we present a lightweight, error-toler...
Saved in:
| Main Authors: | Lekai Song, Pengyu Liu, Jingfang Pei, Yang Liu, Songwei Liu, Shengbo Wang, Leonard W. T. Ng, Tawfique Hasan, Kong-Pang Pun, Shuo Gao, Guohua Hu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59872-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Balanced Ionic‐Electronic Conductors Enabling Organic Electrochemical Memristors
by: Yani Wang, et al.
Published: (2025-06-01) -
Spiking Reservoir Computing Based on Stochastic Diffusive Memristors
by: Zelin Ma, et al.
Published: (2025-03-01) -
Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling
by: Lixia Ye, et al.
Published: (2020-01-01) -
A Passive and Scalable High-Order Neuromorphic Circuit Enabled by Mott Memristors
by: Zikang Lin, et al.
Published: (2025-01-01) -
Stochastic Memristor Modeling Framework Based on Physics-Informed Neural Networks
by: Kyeongmin Kim, et al.
Published: (2024-10-01)