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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 34, Number 3(3) (2022)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 1077-1089
S&M2874 Research Paper of Special Issue https://doi.org/10.18494/SAM3378 Published in advance: June 15, 2021 Published: March 17, 2022 Chip Contour Detection Based on Real-time Image Sensing and Recognition [PDF] Bao-Rong Chang, Hsiu-Fen Tsai, Chia-Wei Hsieh, and Mo-Lan Chen (Received March 28, 2021; Accepted May 26, 2021) Keywords: deep learning, Jetson Nano, object tracking, real-time image sensing and recognition, GSEH-YOLOv5, attention mechanism, SENet, GhostNet
In this study, the GSEH-YOLOv5 (GhostNet and SENet included in Head-YOLOv5) algorithm is used to realize real-time object tracking and image sensing and recognition on the Jetson Nano embedded platform. The purpose is to instantly detect the appearance contour of the chip inside the chip slot. As soon as our system detects the damaged chip, a warning is generated, and the correct location of the damaged chip in the chip slot is labeled. After that, the operator immediately removes the damaged chip to prevent the next chip from being damaged. Finally, we also analyze and compare the performance between the improved GSEH-YOLOv5 algorithm and the traditional YOLOv5 algorithm to verify that the proposed method has the better performance.
Corresponding author: Hsiu-Fen Tsai, Chia-Wei Hsieh  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Bao-Rong Chang, Hsiu-Fen Tsai, Chia-Wei Hsieh, and Mo-Lan Chen, Chip Contour Detection Based on Real-time Image Sensing and Recognition, Sens. Mater., Vol. 34, No. 3, 2022, p. 1077-1089. |
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