TY - GEN
T1 - Massive Figure Extraction and Classification in Electronic Component Datasheets for Accelerating PCB Design Preparation
AU - Chen, Kuan Chun
AU - Lee, Chou Chen
AU - Lin, Po-Hung
AU - Wang, Yan Jhih
AU - Chen, Yi Ting
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/30
Y1 - 2021/8/30
N2 - Before starting printed-circuit-board (PCB) design, it is usually very time-consuming for PCB and system designers to review a large amount of electronic component datasheets in order to determine the best integration of electronic components for the target electronic systems. Each datasheet may contain over hundred figures and tables, while the figures and tables usually present the most important electronic component specifications. This paper categorizes various figures, including tables, in electronic component datasheets, and proposes the ECS-YOLO model for massive figure extraction and classification in order to accelerate PCB design preparation process. The experimental results show that, compared with the state-of-the-art object detection model, the proposed ECS-YOLO can consistently achieve better accuracy for figure extraction and classification in electronic component datasheets.
AB - Before starting printed-circuit-board (PCB) design, it is usually very time-consuming for PCB and system designers to review a large amount of electronic component datasheets in order to determine the best integration of electronic components for the target electronic systems. Each datasheet may contain over hundred figures and tables, while the figures and tables usually present the most important electronic component specifications. This paper categorizes various figures, including tables, in electronic component datasheets, and proposes the ECS-YOLO model for massive figure extraction and classification in order to accelerate PCB design preparation process. The experimental results show that, compared with the state-of-the-art object detection model, the proposed ECS-YOLO can consistently achieve better accuracy for figure extraction and classification in electronic component datasheets.
UR - http://www.scopus.com/inward/record.url?scp=85115726554&partnerID=8YFLogxK
U2 - 10.1109/MLCAD52597.2021.9531275
DO - 10.1109/MLCAD52597.2021.9531275
M3 - Conference contribution
AN - SCOPUS:85115726554
T3 - 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD, MLCAD 2021
BT - 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD, MLCAD 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd ACM/IEEE Workshop on Machine Learning for CAD, MLCAD 2021
Y2 - 30 August 2021 through 3 September 2021
ER -