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Targeted Labeling of Neurons in a Specific Functional Micro-domain of the Neocortex by Combining Intrinsic Signal and Two-photon Imaging
Published on: December 12, 2012
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In-sensor image memorization and encoding via optical neurons for bio-stimulus domain reduction toward visual
Doeon Lee1, Minseong Park1, Yongmin Baek1
1Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA.
Nature Communications
|September 6, 2022
Summary
This study introduces a novel in-sensor computing system using a 1-photodiode and 1 memristor (1P-1R) crossbar. This system enables efficient visual cognitive processing directly within sensors, reducing data transfer for machine vision applications.
Area of Science:
- Neuromorphic Engineering
- Computer Vision
- Materials Science
Background:
- Machine vision systems generate vast data, necessitating efficient computational processing.
- In-sensor computing offers a solution for reduced data transfer and enhanced energy efficiency in visual processing.
- Current in-sensor systems cannot process images stored directly within the sensor.
Purpose of the Study:
- To demonstrate a heterogeneously integrated 1-photodiode and 1 memristor (1P-1R) crossbar for in-sensor visual cognitive processing.
- To emulate mammalian image encoding for feature extraction directly on the sensor.
- To advance the in-sensor computing paradigm by applying trained weights as input voltage.
Main Methods:
- Heterogeneous integration of a 1-photodiode and 1 memristor (1P-1R) into a crossbar array.
- Emulation of mammalian image encoding processes for feature extraction.
- Application of trained weight values as input voltage to the image-saved crossbar array.
Main Results:
- Successful demonstration of an in-sensor computing platform capable of processing stored images.
- Feature extraction from input images emulating biological visual processing.
- Realization of the in-sensor computing paradigm without storing weight values in memristors.
Conclusions:
- The developed 1P-1R crossbar enables direct in-sensor visual cognitive processing.
- This platform offers an advanced architecture for real-time, data-intensive machine vision.
- Bio-stimulus domain reduction enhances efficiency for machine vision applications.
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