ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment

With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effective way of inspecting the quality of printed texts on chip components. The major problem that deters this area of researc...

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Main Authors: Ng, Chun Chet, Bin Nazaruddin, Akmalul Khairi, Lee, Yeong Khang, Wang, Xinyu, Liu, Yuliang, Chan, Chee Seng, Jin, Lianwen, Sun, Yipeng, Fan, Lixin
Format: Conference or Workshop Item
Published: 2021
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Online Access:http://eprints.um.edu.my/35412/
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spelling my.um.eprints.354122023-10-17T07:43:15Z http://eprints.um.edu.my/35412/ ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment Ng, Chun Chet Bin Nazaruddin, Akmalul Khairi Lee, Yeong Khang Wang, Xinyu Liu, Yuliang Chan, Chee Seng Jin, Lianwen Sun, Yipeng Fan, Lixin QA76 Computer software With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effective way of inspecting the quality of printed texts on chip components. The major problem that deters this area of research is the lacking of realistic text on chips datasets to act as a strong foundation. Hence, a text on chips dataset, ICText is used as the main target for the proposed Robust Reading Challenge on Integrated Circuit Text Spotting and Aesthetic Assessment (RRC-ICText) 2021 to encourage the research on this problem. Throughout the entire competition, we have received a total of 233 submissions from 10 unique teams/individuals. Details of the competition and submission results are presented in this report. 2021 Conference or Workshop Item PeerReviewed Ng, Chun Chet and Bin Nazaruddin, Akmalul Khairi and Lee, Yeong Khang and Wang, Xinyu and Liu, Yuliang and Chan, Chee Seng and Jin, Lianwen and Sun, Yipeng and Fan, Lixin (2021) ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment. In: 16th International Conference on Document Analysis and Recognition, ICDAR 2021, 5 - 10 September 2021, Lausanne.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA76 Computer software
spellingShingle QA76 Computer software
Ng, Chun Chet
Bin Nazaruddin, Akmalul Khairi
Lee, Yeong Khang
Wang, Xinyu
Liu, Yuliang
Chan, Chee Seng
Jin, Lianwen
Sun, Yipeng
Fan, Lixin
ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
description With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effective way of inspecting the quality of printed texts on chip components. The major problem that deters this area of research is the lacking of realistic text on chips datasets to act as a strong foundation. Hence, a text on chips dataset, ICText is used as the main target for the proposed Robust Reading Challenge on Integrated Circuit Text Spotting and Aesthetic Assessment (RRC-ICText) 2021 to encourage the research on this problem. Throughout the entire competition, we have received a total of 233 submissions from 10 unique teams/individuals. Details of the competition and submission results are presented in this report.
format Conference or Workshop Item
author Ng, Chun Chet
Bin Nazaruddin, Akmalul Khairi
Lee, Yeong Khang
Wang, Xinyu
Liu, Yuliang
Chan, Chee Seng
Jin, Lianwen
Sun, Yipeng
Fan, Lixin
author_facet Ng, Chun Chet
Bin Nazaruddin, Akmalul Khairi
Lee, Yeong Khang
Wang, Xinyu
Liu, Yuliang
Chan, Chee Seng
Jin, Lianwen
Sun, Yipeng
Fan, Lixin
author_sort Ng, Chun Chet
title ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
title_short ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
title_full ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
title_fullStr ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
title_full_unstemmed ICDAR 2021 competition on integrated circuit text spotting and aesthetic assessment
title_sort icdar 2021 competition on integrated circuit text spotting and aesthetic assessment
publishDate 2021
url http://eprints.um.edu.my/35412/
_version_ 1781704465310547968
score 13.18916