An imbalance handling method to improve the detection and classification of symbols depicted in Piping and Instrumentation Diagrams (P&IDs)
See demo.ipynb for a jupyter notebook demo on how to use this method.
The original symbol dataset can be downloaded from here: https://www.dropbox.com/s/sj277k4slmrv3qc/symbols_combined_pixel_red.csv?dl=0
The generated symbol dataset, once CDSMOTE has been applied, can be downloaded from here: https://www.dropbox.com/s/ll562q3gjqyrhp9/cdsmotedb_symbols_combined_pixel_kmeans.csv?dl=0
Please reference this method as follows:
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E. Elyan, C. F. Moreno-García & P. Johnston, “Symbols in Engineering Drawings (SiED): An imbalanced dataset benchmarked by convolutional neural networks”, Engineering Applications of Neural Networks (EANN) 2020, Halkidiki, Greece, INNS 2, pp. 215–224. https://doi.org/10.1007/978-3-030-48791-1_16.
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L. Jamieson, C. F. Moreno-García & E. Elyan, “A multiclass imbalanced dataset classification of symbols from piping and instrumentation diagrams”, In: Barney Smith, E.H., Liwicki, M., Peng, L. (eds). International Conference on Document Analysis and Recognition (ICDAR 2024). Lecture Notes in Computer Science, vol 14804, pp. 3-16. Springer, Cham. https://doi.org/10.1007/978-3-031-70533-5_1.
or use the BibTex entries below:
@inproceedings{Elyan2020, author = {Elyan, Eyad and Moreno-Garc{'{i}}a, Carlos Francisco and Johnston, Pamela}, booktitle = {Engineering Applications of Neural Networks (EANN)}, doi = {10.1007/978-3-030-48791-1}, isbn = {9783030487911}, keywords = {Imbalance,P&ID,classification,cnn,engineering drawings,id,imbalanced dataset,multiclass,p}, mendeley-tags = {Imbalance,P&ID}, pages = {215--224}, title = {{Symbols in Engineering Drawings (SiED): An Imbalanced Dataset Benchmarked by Convolutional Neural Networks}}, year = {2020} }
@inproceedings{Jamieson2024, author = {Jamieson, Laura and Moreno-Garc{'{i}}a, Carlos Francisco and Elyan, Eyad}, booktitle = {International Conference on Document Analysis and Recognition (ICDAR)}, doi = {10.1007/978-3-031-70533-5}, isbn = {9783031705335}, keywords = {convolutional neural networks,piping and instrumentation diagrams}, pages = {3--16}, title = {{A Multiclass Imbalanced Dataset Classification of Symbols from Piping and Instrumentation Diagrams}}, year = {2024} }