In-sensor image memorization and encoding via optical neurons for bio-stimulus domain reduction toward visual cognitive processing.
Nat Commun
; 13(1): 5223, 2022 09 05.
Article
in En
| MEDLINE
| ID: mdl-36064944
ABSTRACT
As machine vision technology generates large amounts of data from sensors, it requires efficient computational systems for visual cognitive processing. Recently, in-sensor computing systems have emerged as a potential solution for reducing unnecessary data transfer and realizing fast and energy-efficient visual cognitive processing. However, they still lack the capability to process stored images directly within the sensor. Here, we demonstrate a heterogeneously integrated 1-photodiode and 1 memristor (1P-1R) crossbar for in-sensor visual cognitive processing, emulating a mammalian image encoding process to extract features from the input images. Unlike other neuromorphic vision processes, the trained weight values are applied as an input voltage to the image-saved crossbar array instead of storing the weight value in the memristors, realizing the in-sensor computing paradigm. We believe the heterogeneously integrated in-sensor computing platform provides an advanced architecture for real-time and data-intensive machine-vision applications via bio-stimulus domain reduction.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Vision, Ocular
/
Neurons
Limits:
Animals
Language:
En
Journal:
Nat Commun
Journal subject:
BIOLOGIA
/
CIENCIA
Year:
2022
Type:
Article
Affiliation country:
United States