Multi-Task Classification of Sewer Pipe Defects and Properties using a Cross-Task Graph Neural Network Decoder

Joakim Bruslund Haurum, Meysam Madadi, Sergio Escalera Guerrero, Thomas B. Moeslund

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

4 Citations (Scopus)

4 Citations
2 Journal article
1 Article in proceeding

3 results

2022
Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification
Haurum, J. B., Madadi, M., Guerrero, S. E. & Moeslund, T. B., Dec 2022, In: Automation in Construction. 144, 104614.
Research output: Contribution to journal › Journal article › Research › peer-review

Open Access
File
4 Citations (Scopus)

233 Downloads (Pure)
2021
Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark
Haurum, J. B. & Moeslund, T. B., 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): IEEE, p. 13451-13462 12 p. 9577322. (I E E E Conference on Computer Vision and Pattern Recognition. Proceedings).
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Open Access
30 Citations (Scopus)
2020
Water Level Estimation in Sewer Pipes using Deep Convolutional Neural Networks
Haurum, J. B., Bahnsen, C. H., Pedersen, M. & Moeslund, T. B., 4 Dec 2020, In: Water. 12, 12, 14 p., 3412.
Research output: Contribution to journal › Journal article › Research › peer-review

Open Access
File
15 Citations (Scopus)

101 Downloads (Pure)