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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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. |
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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 |
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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/ |
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1781704465310547968 |
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13.18916 |