@String(PAMI = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV = {Int. J. Comput. Vis.})
@String(CVPR= {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV= {Int. Conf. Comput. Vis.})
@String(ECCV= {Eur. Conf. Comput. Vis.})
@String(NIPS= {Adv. Neural Inform. Process. Syst.})
@String(ICPR = {Int. Conf. Pattern Recog.})
@String(BMVC= {Brit. Mach. Vis. Conf.})
@String(TOG= {ACM Trans. Graph.})
@String(TIP  = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TMM  = {IEEE Trans. Multimedia})
@String(ACMMM= {ACM Int. Conf. Multimedia})
@String(ICME = {Int. Conf. Multimedia and Expo})
@String(ICASSP=	{ICASSP})
@String(ICIP = {IEEE Int. Conf. Image Process.})
@String(ACCV  = {ACCV})
@String(ICLR = {Int. Conf. Learn. Represent.})
@String(IJCAI = {IJCAI})
@String(PR   = {Pattern Recognition})
@String(AAAI = {AAAI})
@String(CVPRW= {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(CSVT = {IEEE Trans. Circuit Syst. Video Technol.})

@String(SPL	= {IEEE Sign. Process. Letters})
@String(VR   = {Vis. Res.})
@String(JOV	 = {J. Vis.})
@String(TVC  = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
@String(CGF  = {Comput. Graph. Forum})
@String(CVM = {Computational Visual Media})


@String(PAMI  = {IEEE TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(NIPS  = {NeurIPS})
@String(ICPR  = {ICPR})
@String(BMVC  =	{BMVC})
@String(TOG   = {ACM TOG})
@String(TIP   = {IEEE TIP})
@String(TVCG  = {IEEE TVCG})
@String(TCSVT = {IEEE TCSVT})
@String(TMM   =	{IEEE TMM})
@String(ACMMM = {ACM MM})
@String(ICME  =	{ICME})
@String(ICASSP=	{ICASSP})
@String(ICIP  = {ICIP})
@String(ACCV  = {ACCV})
@String(ICLR  = {ICLR})
@String(IJCAI = {IJCAI})
@String(PR = {PR})
@String(AAAI = {AAAI})
@String(CVPRW= {CVPRW})
@String(CSVT = {IEEE TCSVT})



@misc{Authors14,
 author = {FirstName LastName},
 title = {The frobnicatable foo filter},
 note = {Face and Gesture submission ID 324. Supplied as supplemental material {\tt fg324.pdf}},
 year = 2014
}

@misc{Authors14b,
 author = {FirstName LastName},
 title = {Frobnication tutorial},
 note = {Supplied as supplemental material {\tt tr.pdf}},
 year = 2014
}

@article{Alpher02,
author = {FirstName Alpher},
title = {Frobnication},
journal = PAMI,
volume = 12,
number = 1,
pages = {234--778},
year = 2002
}

@article{Alpher03,
author = {FirstName Alpher and  FirstName Fotheringham-Smythe},
title = {Frobnication revisited},
journal = {Journal of Foo},
volume = 13,
number = 1,
pages = {234--778},
year = 2003
}

@article{Alpher04,
author = {FirstName Alpher and FirstName Fotheringham-Smythe and FirstName Gamow},
title = {Can a machine frobnicate?},
journal = {Journal of Foo},
volume = 14,
number = 1,
pages = {234--778},
year = 2004
}

@inproceedings{Alpher05,
author = {FirstName Alpher and FirstName Gamow},
title = {Can a computer frobnicate?},
booktitle = ICCV,
pages = {234--778},
year = 2005
}
% Agricultural Field Boundary Detection - South Asia

@article{persello2019delineation,
  author = {Persello, Claudio and Tolpekin, Valentyn A. and Bergado, John Ray and de Bie, C. A. J. M.},
  title = {Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping},
  journal = {Remote Sensing of Environment},
  volume = {231},
  pages = {111253},
  year = {2019},
  publisher = {Elsevier},
  doi = {10.1016/j.rse.2019.111253}
}

@article{yang2020bangladesh,
  author = {Yang, Dalei and Fang, Shenghui and Cui, Ruishan and others},
  title = {Deep learning approach for segmenting functional field units in {B}angladesh smallholder farms},
  journal = {Remote Sensing Applications: Society and Environment},
  volume = {20},
  year = {2020},
  publisher = {Elsevier}
}

@article{wang2022india,
  author = {Wang, Sherrie and Waldner, Fran\c{c}ois and Lobell, David B.},
  title = {Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision},
  journal = {Remote Sensing},
  volume = {14},
  number = {22},
  pages = {5738},
  year = {2022},
  publisher = {MDPI},
  doi = {10.3390/rs14225738}
}

@article{persello2023ai4smallfarms,
  author = {Persello, Claudio and Grift, Jordi and Fan, Xuran and others},
  title = {{AI4SmallFarms}: A Dataset for Crop Field Delineation in {S}outheast {A}sian Smallholder Farms},
  journal = {IEEE Geoscience and Remote Sensing Letters},
  volume = {20},
  year = {2023},
  publisher = {IEEE},
  doi = {10.1109/LGRS.2023.3322937}
}

@article{kerner2024fields,
  author = {Kerner, Hannah and Chaudhari, Snehal and Ghosh, Aninda and others},
  title = {Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation},
  journal = {arXiv preprint arXiv:2409.16252},
  year = {2024}
}

@article{joshi2023nepal,
  author = {Joshi, R. and others},
  title = {{UAV} imagery and {ENVI} edge-detection for land parcel delineation in {N}epal's {T}erai and hills},
  journal = {Journal of Geoinformatics, Nepal},
  year = {2023}
}

% Foundation Models in Remote Sensing

@article{osco2023sam,
  author = {Osco, Lucas Prado and Wu, Qiusheng and de Lemos, Eduardo Lopes and others},
  title = {The Segment Anything Model ({SAM}) for Remote Sensing Applications: From Zero to One Shot},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  volume = {124},
  pages = {103540},
  year = {2023},
  publisher = {Elsevier},
  doi = {10.1016/j.jag.2023.103540}
}

@article{lefebvre2025tree,
  author = {Lefebvre, Maxime and Laliberté, Etienne},
  title = {Assessing {SAM} for Tree Crown Instance Segmentation from Drone Imagery},
  journal = {arXiv preprint arXiv:2503.20199},
  year = {2025}
}

@article{chen2024rsprompter,
  author = {Chen, Keyan and Liu, Chenyang and Chen, Hao and Zhang, Haotian and Li, Wenyuan and Zou, Zhengxia and Shi, Zhenwei},
  title = {{RSPrompter}: Learning to Prompt for Remote Sensing Instance Segmentation Based on Visual Foundation Model},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  volume = {62},
  pages = {1--17},
  year = {2024},
  publisher = {IEEE},
  doi = {10.1109/TGRS.2024.3356074}
}

@article{moghimi2024sam,
  author = {Moghimi, Armin and Welzel, Mario and Celik, Turgay and Schlurmann, Torsten},
  title = {A Comparative Performance Analysis of Popular Deep Learning Models and Segment Anything Model ({SAM}) for River Water Segmentation in Close-Range Remote Sensing Imagery},
  journal = {IEEE Access},
  volume = {12},
  pages = {52067--52085},
  year = {2024},
  publisher = {IEEE},
  doi = {10.1109/ACCESS.2024.3386654}
}

@article{lavreniuk2025delineate,
  author = {Lavreniuk, Mykola and Kussul, Nataliia and Shelestov, Andrii and others},
  title = {Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery},
  journal = {arXiv preprint arXiv:2504.02534},
  year = {2025}
}

% Multi-Paradigm Segmentation and UAV Methods

@article{weyler2024phenobench,
  author = {Weyler, Jan and Magistri, Federico and Marks, Elias and others},
  title = {{PhenoBench} -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume = {46},
  number = {12},
  pages = {9583--9594},
  year = {2024},
  publisher = {IEEE},
  doi = {10.1109/TPAMI.2024.3449762}
}

@article{sprute2025lulc,
  author = {Sprute, T. and others},
  title = {Land use and land cover classification on high-resolution {UAV} images for heavy rainfall hazard maps using deep neural networks},
  journal = {Remote Sensing Applications: Society and Environment},
  volume = {41},
  pages = {101609},
  year = {2025},
  publisher = {Elsevier},
  doi = {10.1016/j.rsase.2025.101609}
}

@article{spasev2024segformer,
  author = {Spasev, Dimche and others},
  title = {Semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images using {SegFormer}},
  journal = {arXiv preprint arXiv:2410.01092},
  year = {2024}
}

@article{zhao2025landunet,
  author = {Zhao, Zehui and others},
  title = {{Land-UNet}: A deep learning network for precise segmentation and identification of non-structured land use types in rural areas for green urban space analysis},
  journal = {Ecological Informatics},
  volume = {85},
  pages = {102871},
  year = {2025},
  publisher = {Elsevier},
  doi = {10.1016/j.ecoinf.2025.102871}
}

@article{dua2024india,
  author = {Dua, Rohit and others},
  title = {Agricultural Landscape Understanding At Country-Scale},
  journal = {arXiv preprint arXiv:2411.05359},
  year = {2024}
}

@article{tripathy2024sam,
author = {Tripathy, Pratyush and Baylis, Kathy and Wu, Kyle and Watson, Jyles and Jiang, Ruizhe},
title = {Investigating the Segment Anything Foundation Model for Mapping Smallholder Agriculture Field Boundaries Without Training Labels},
journal = {arXiv preprint arXiv:2407.01846},
year = {2024}
}

@inproceedings{chang2024foundation,
author = {Chang, Yi-Chia and Stewart, Adam J. and Bastani, Favyen and Wolters, Piper and Kannan, Shreya and Huber, George R. and Wang, Jingtong and Banerjee, Arindam},
title = {On the Generalizability of Foundation Models for Crop Type Mapping},
booktitle = {IEEE Int. Geosci. Remote Sens. Symp. (IGARSS)},
year = {2025}
}

@misc{roboflow2024,
  author = {{Roboflow}},
  title = {Roboflow: Computer Vision Annotation and Deployment Platform},
  year = {2024},
  url = {https://roboflow.com},
  note = {Accessed: January 2026}
}
