1 |
Redmon, J. and Farhadi, A. (2017), "YOLO9000: better, faster, stronger", Computer Vision and Pattern Recognition, arXiv:1612.08242.
|
2 |
Ren, S., He, K., Girshick, R. and Sun, J. (2015), "Faster R-CNN: towards real-time object detection with region proposal networks", Adv. Neural Inform. Process. Syst., 91-99.
|
3 |
Zhang, R., Yao, J., Zhang, K., Feng, C. and Zhang, J. (2016), "S-CNN-based ship detection from highresolution remote sensing images", International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41, https://ui.adsabs.harvard.edu/link_gateway/2016ISPAr41B7..423Z/doi:10.5194/isprs-archives-XLI-B7-423-2016.
DOI
|
4 |
Girshick, R., Donahue, J., Darrell, T. and Malik, J. (2014), "Rich feature hierarchies for accurate object detection and semantic segmentation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 580-587.
|
5 |
Hermann, D., Galeazzi, R., Andersen, J.C. and Blanke, M. (2015), "Smart sensor based obstacle detection for high-speed unmanned surface vehicle", IFAC Workshop Series, 48(16), 190-197.
|
6 |
Huang, J., Rathod, V., Sun, C., Zhu, M., Korattikara, A., Fathi, A., Fischer, I., Wojna, Z., Song, Y., Guadarrama, S. and Murphy, K. (2016), "Speed/accuracy trade-offs for modern convolutional object detectors", arXiv preprint arXiv, 1611.10012.
|
7 |
ImageNet (2019), URL http://www.image-net.org//
|
8 |
Lee, J.M., Lee, K.H., Nam, B. and Wu, Y. (2016), "Study on image-based ship detection for AR navigation", Proceedings of the 6th International Conference on IT Convergence and Security, ICITCS, 1-4.
|
9 |
Cuong, D.D., Hua, X. and Morere, O. (2015), "Maritime vessel images classification using deep convolutional neural networks", Proceedings of the 6th International Symposium on Information and Communication Technology, 276-281.
|
10 |
Everingham, M., Eslami, S.M.A., Van-Gool, L., Williams, C.K.I., Winn, J. and Zisserman, A. (2015), "The PASCAL visual object classes challenge: a retrospective", Int. J. Comput. Vision, 111(1), 98-136.
DOI
|
11 |
Lee, S.J., Roh, M.I., Lee, H.W., Ha, J.S. and Woo, I.G. (2018), "Image-based ship detection and classification for unmanned surface vehicle using real-time object detection neural networks", Proceedings of the International Society of Offshore and Polar Engineers 2018, Sapporo, Japan.
|
12 |
Mass, A.L., Hannun, A.Y. and Ng, A.Y. (2013), "Rectifier nonlinearities improve neural network acoustic models", Proceedings of the 30th International Conference on Machine Learning, JMLR: W&CP volume 28.
|
13 |
Lee, S.J., Roh, M.I., Oh, M.J., Seok, Y.S., Lee, W.J., Lee, J.B. and Kim, H.S. (2019), "Image-based object detection and tracking method for ship navigation," Proceedings of International Conference on Computer Applications in Shipbuilding 2019, Rotterdam, Netherlands.
|
14 |
Lin, M., Chen, Q. and Yan, S. (2013), "Network in network," arXiv:1312.4400.
|
15 |
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y. and Berg, A.C. (2016), "SSD: single shot multibox detector", Proceedings of European Conference on Computer Vision, Springer, Cham.
|
16 |
Pan, S.J. and Yang, Q. (2010), "A survey on transfer learning", IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359.
DOI
|
17 |
Prasad, D.K., Rajan, D., Rachmawati, L., Rajabaly, E. and Quek, C. (2017), "Video processing from electrooptical sensors for object detection and tracking in maritime environment: a survey", IEEE T. Intel. Transport. Syst., 18(8), 1993-2016.
DOI
|
18 |
Redmon, J., Divvala, S., Girshick, R. and Farhadi, A. (2016), "You only look once: unified, real-time object detection", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
|