Related Experiment Video
Updated: Mar 1, 2026
10:50
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
Published on: June 21, 2022
2.2K
Recent Advances and Perspectives on Field-Effect Transistors for Artificial Visual Neuromorphic Systems
Liu Yaqian1,2,3, Lang Menghua1, Xu Yihang1
1School of Electronics and Information, Zhengzhou University of Light Industry, Zhengzhou, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|February 27, 2026
Summary
Field-effect transistors (FETs) offer a path beyond the limitations of traditional computing architectures. These devices are crucial for developing energy-efficient, bio-inspired visual neuromorphic systems.
Area of Science:
- Materials Science
- Computer Engineering
- Neuroscience
Background:
- The von Neumann architecture faces limitations in computational efficiency and energy consumption due to exponential data growth.
- Biological visual systems offer a model for highly integrated, energy-efficient, and multimodal processing.
- Field-effect transistors (FETs) are promising for neuromorphic systems due to their optoelectronic properties and low power usage.
Purpose of the Study:
- To provide a comprehensive review of FET-based visual neuromorphic systems.
- To detail the role of FETs in emulating biological visual functions.
- To discuss challenges and future prospects in FET-mediated perception for bio-inspired electronics.
Main Methods:
- Review of semiconductor material selection for FETs.
- Analysis of fundamental FET device architectures and operational principles.
- Examination of FETs in emulating biological visual functions.
Main Results:
- FETs are a leading platform for visual neuromorphic systems, offering tunability and flexibility.
- The review covers device design, operation, and emulation of biological vision.
- Key challenges and future directions for FET-based perception are identified.
Conclusions:
- FETs are essential for developing next-generation artificial visual systems.
- This research provides insights for designing advanced bio-inspired electronics.
- Further development in FETs can overcome current limitations in intelligent computing.
