ICIP 2021 paper on Surface Defect Recognition #10
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Hi. Vikanksh Nath wellcome all your fantastic work on this forum. but this url does not work, please check it. |
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May be it's due to location. Kindly see the below link: |
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Dear Connections,
I hope you are doing well.
I am happy to share that our #research work has been accepted in 2021 IEEE International Conference on Image Processing (ICIP), 19-22 September 2021 • Anchorage, Alaska, USA
and available at below link as an open preview.
https://lnkd.in/gW-t_qEg
Or
https://ieeexplore.ieee.org/document/9506405
● In this work we have proposed S2D2Net, an automatic defect recognition network for surface defect diagnosis, achieving SOTA results on publicly available steel surface defect datasets (NEU-CLS and extended diversified dataset ENEU).
Our method utilizes CapsNet over extracted feature maps from a pretrained ImageNet model, enabling faster training, robustness, and learning with very few samples.
● We welcome researchers working in different vision domains to analyse the scope of our hybrid technique in thier own applications targeting small sample problems along with robustness.
I invite readers to please review, and cite our work if found useful.
Thanks.
P.S. ICIP is a tier-A core CSE Conference having h5-index>60 on Google Scholar metrics, and features among the top publication under "Computer Vision and Pattern Recognition" category.
Links:
Google Scholar:
https://scholar.google.co.in/citations?view_op=top_venues&hl=en&vq=eng_computervisionpatternrecognition
Top Conferences in Core CSE:
http://cic.tju.edu.cn/faculty/zhileiliu/doc/COREComputerScienceConferenceRankings.html
ICIP 2021 official site:
https://www.2021.ieeeicip.org/
#artificialintelligence #computervision #ai #industria40 #deeplearning #ieeexplore #vision #visioninspection #AI #computervision #deeplearning #TensorFlow #surfacepattern #patternrecognition
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