| Paper Abstract and Keywords |
| Presentation |
2021-08-17 13:55
Study of an Event-Driven CMOS Image Sensor Using Deep Learning (1)
-- Verification of Image Classification Using Low Bit-Resolution Feature Images --
Kohei Yamamoto, Kota Yoshida, Shunsuke Okura (Ritsumeikan Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Currently, CMOS image sensors are expected to be integrated with AI using deep learning to create new technologies.
Conventional image sensors output image data with a large amount of information for humans to appreciate as photographs.
However, there is a lo t of useless and unnecessary data for AI to use for image recognition, which is thought to lead to increased power consumption and latency of the entire system.
Therefore, we thought it would be possible to reduce the power consumption of image sensors if image sensors could output images with a small amount of information when performing image recognition and AI could perform recognition.
In this paper, we examined the pixel configuration that enables feature extraction using photoelectric conversion electrons, and verified whether image classification is possible.
We also examined the effect of the bit resolution of the image obtained by intra-pixel arithmetic on the recognition rate of the image in order to achieve low power consumption during the feature extraction operation. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
CMOS / feature extraction / intra-pixel arithmetic / histogram equalization / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 45, no. 21, IST2021-43, pp. 29-33, Aug. 2021. |
| Paper # |
IST2021-43 |
| Date of Issue |
2021-08-10 (IST) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
IEICE-SDM IEICE-ICD IST |
| Conference Date |
2021-08-17 - 2021-08-18 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Analog, Mixed Analog and Digital, RF, and Sensor Interface, Low Voltage/Low Power Techniques, Novel Devices/Circuits, and the Applications |
| Paper Information |
| Registration To |
IST |
| Conference Code |
2021-08-SDM-ICD-IST |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Study of an Event-Driven CMOS Image Sensor Using Deep Learning (1) |
| Sub Title (in English) |
Verification of Image Classification Using Low Bit-Resolution Feature Images |
| Keyword(1) |
CMOS |
| Keyword(2) |
feature extraction |
| Keyword(3) |
intra-pixel arithmetic |
| Keyword(4) |
histogram equalization |
| Keyword(5) |
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| 1st Author's Name |
Kohei Yamamoto |
| 1st Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
| 2nd Author's Name |
Kota Yoshida |
| 2nd Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
| 3rd Author's Name |
Shunsuke Okura |
| 3rd Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2021-08-17 13:55:00 |
| Presentation Time |
25 minutes |
| Registration for |
IST |
| Paper # |
IST2021-43 |
| Volume (vol) |
vol.45 |
| Number (no) |
no.21 |
| Page |
pp.29-33 |
| #Pages |
5 |
| Date of Issue |
2021-08-10 (IST) |
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