Leveraging multiple datasets for deep leaf counting
Dobrescu, Andrei; Giuffrida, Mario Valerio; Tsaftaris, Sotirios A;
Subject: Computer Science - Computer Vision and Pattern Recognition
The number of leaves a plant has is one of the key traits (phenotypes) describing its development and growth. Here, we propose an automated, deep learning based approach for counting leaves in model rosette plants. While state-of-the-art results on leaf counting with de... View more
 C. Arteta, V. Lempitsky, J. A. Noble, and A. Zisserman. Interactive Object Counting. pages 504-518, 2014.
 C. Arteta, V. Lempitsky, and A. Zisserman. Counting in the Wild. 1:483-498, 2016.
 J. Bell and H. Dee. Aberystwyth Leaf Evaluation Dataset, 2016.
 A. Chayeb, N. Ouadah, Z. Tobal, M. Lakrouf, and O. Azouaoui. Hog based multi-object detection for urban navigation. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pages 2962-2967, 2014.
 J. A. Cruz, X. Yin, X. Liu, S. M. Imran, D. D. Morris, D. M. Kramer, and J. Chen. Multi-modality imagery database for plant phenotyping. Machine Vision and Applications, 27(5):735-749, 2016.
 N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), volume 1, pages 886-893 vol. 1, June 2005.
 J. Donahue, L. Anne Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell. Long-term recurrent convolutional networks for visual recognition and description. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015.
 L. Fiaschi, R. Nair, U. Koethe, and F. A. Hamprecht. Learning to Count with Regression Forest and Structured Labels. In 21st International Conference on Pattern Recognition (ICPR 2012), pages 2685-2688, 2012.
 R. Girshick. Fast r-cnn. In The IEEE International Conference on Computer Vision (ICCV), December 2015.
 R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.