Publications
1) J. Guo, C. Yang, E. Cai, and E. J. Delp, "Rotation Adaptive Plot Extraction from UAV RGB Images", Proceedings of the IEEE International Symposium on Geoscience and Remote Sensing, July 2023, Pasadena, CA.
2) E. Cai, J. Guo, C. Yang, and E. J. Delp, "Semi-Supervised Object Detection for Sorghum Panicles in UAV Imagery", Proceedings of the IEEE International Symposium on Geoscience and Remote Sensing, July 2023, Pasadena, CA.
3) E. Cai, Z. Luo, S. Baireddy, J. Guo, C. Yang, and E. J. Delp, "High-Resolution UAV Image Generation for Sorghum Panicle Detection", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), the 3rd International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture, June 2022, New Orleans, LA. arXiv:2205.03947
4) C. Yang, S. Baireddy, E. Cai, M. Crawford, and E. J. Delp, "Field-Based Plot Extraction Using UAV RGB Images", Proceedings of the IEEE International Conference on Computer Vision(ICCV), Workshop on Computer Vision in Plant Phenotyping and Agriculture(CVPPA), October 2021, Montreal, Canada. doi:10.1109/ICCVW54120.2021.00160 arXiv:2109.00632
5) E. Cai, S. Baireddy, C. Yang, M. Crawford, and E. J. Delp, "Panicle Counting in UAV Images For Estimating Flowering Time in Sorghum", Proceedings of the IEEE International Symposium on Geoscience and Remote Sensing, July 2021, Brussels, Belgium. doi:10.1109/IGARSS47720.2021.9554291 arXiv:2107.07308
6) E. Cai, S. Baireddy, C. Yang, M. Crawford, and E. J. Delp, "Deep Transfer Learning For Plant Center Localization", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, the 1st International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture, June 2020, Seattle, WA. doi:10.1109/CVPRW50498.2020.00039
7) J. Ribera, D. Guera, Y. Chen, and E. J. Delp, "Locating Objects Without Bounding Boxes", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019, Long Beach, CA. doi:10.1109/CVPR.2019.00664
8) Y. Chen, S. Baireddy, E. Cai, C. Yang, and E. J. Delp, "Leaf Segmentation by Functional Modeling", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Computer Vision Problems in Plant Phenotyping, June 2019, Long Beach, CA. doi:10.1109/CVPRW.2019.00326
9) Y. Chen, J. Ribera, and E. J. Delp, "Estimating Plant Centers Using A Deep Binary Classifier", Proceedings of the Southwest Symposium on Image Analysis and Interpretation (SSIAI), April 2018, Las Vegas, NV. doi:10.1109/SSIAI.2018.8470367
10) J. Ribera, Y. Chen, C. Boomsma, and E. J. Delp, "Counting Plants Using Deep Learning", Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), November 2017, Montreal, Canada. doi:10.1109/GlobalSIP.2017.8309180
11) Y. Chen, J. Ribera, C. Boomsma, and E. J. Delp, "Locating Crop Plant Centers from UAV-Based RGB Imagery", Proceedings of the IEEE International Conference on Computer Vision, Workshop on Computer Vision Problems in Plant Phenotyping, October 2017, Venice, Italy. doi:10.1109/ICCVW.2017.238
12) Y. Chen, J. Ribera, C. Boomsma, and E. J. Delp, "Plant Leaf Segmentation For Estimating Phenotypic Traits", Proceedings of the IEEE International Conference on Image Processing (ICIP), September 2017, Beijing, China. doi:10.1109/ICIP.2017.8297010
13) J. Ribera, F. He, Y. Chen, A. F. Habib, and E. J. Delp, "Estimating Phenotypic Traits From UAV Based RGB Imagery", Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Workshop on Data Science for Food, Energy, and Water, August 2016, San Francisco, CA. arXiv:1807.00498
Thesis
1) Y. Chen, "Estimating Plant Phenotypic Traits From RGB Imagery", Ph.D dissertation, Purdue University, West Lafayette, IN, December 2019.
2) J. Ribera, "Image-Based Plant Phenotyping Using Machine Learning", Ph.D dissertation, Purdue University, West Lafayette, IN, May 2019.
The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000593. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.