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“SELECTING IMAGE SENSORS FOR EMBEDDED VISION APPLICATIONS: THREE CASE STUDIES,”
FROM AVNET

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Edge AI and Vision Alliance
Edge AI and Vision Alliance
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49 views 1 month ago
49 views • Dec 19, 2023

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Monica Houston, Technical Solutions Manager at Avnet, presents the “Selecting
Image Sensors for Embedded Vision Applications: Three Case Studies,” tutorial at
the May 2023 Embedded Vision Summit.  …...more
...more


TRANSCRIPT

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“SELECTING IMAGE SENSORS FOR EMBEDDED VISION APPLICATIONS: THREE CASE STUDIES,”
FROM AVNET

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49 views49 views
Dec 19, 2023

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DESCRIPTION






“Selecting Image Sensors for Embedded Vision Applications: Three Case Studies,”
from Avnet
Edge AI and Vision Alliance
Edge AI and Vision Alliance
1 Likes
Dec 19 2023
Monica Houston, Technical Solutions Manager at Avnet, presents the “Selecting
Image Sensors for Embedded Vision Applications: Three Case Studies,” tutorial at
the May 2023 Embedded Vision Summit. Selecting the appropriate type of image
sensor is essential for reliable and accurate performance of vision
applications. In this talk, Houston explores some of the critical factors to
consider in selecting an image sensor, including shutter type, dynamic range,
resolution and chromaticity. She explores the impact of these factors through
three distinct use cases: defect detection, license plate recognition and crowd
counting. For defect detection, Houston examines the advantages and
disadvantages of monochrome image sensors. In license plate recognition, she
highlights the importance of global shutter, pixel size, dynamic range and color
space, providing a comprehensive introduction to key factors that contribute to
successful recognition in varying light conditions. Lastly, she explores the
trade-offs of high-resolution cameras in crowd counting applications and offers
practical insights on developing fast and accurate machine learning models with
high-resolution input.
Show less Show more


TRANSCRIPT

Follow along using the transcript.

Show transcript



EDGE AI AND VISION ALLIANCE

4.48K subscribers
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