@article {11573/1616179,
	title = {{Augmentation of Sunflower-Weed Segmentation Classification with Unity Generated Imagery Including Near Infrared Sensor Data}},
	volume = {{False}},
	number = {{False}},
	year = {2022},
	pages = {42-63},
	keywords = {Plant-weed Segmentation Classification, Unity Engine}, {Near Infrared},
	doi = {{10.1007/978-3-030-84811-8\_3}},
	author = {Carbone, Carlos and Potena, Ciro and Nardi, Daniele}
}
@article {11573/1220042,
	title = {{AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming}},
	journal = {IEEE ROBOTICS AND AUTOMATION LETTERS},
	volume = {{4}},
	number = {{2}},
	year = {2019},
	pages = {1085-1092},
	keywords = {robotics in agriculture and forestry}, {multi-robot systems},
	doi = {{10.1109/LRA.2019.2894468}},
	author = {Potena, Ciro and Khanna, Raghav and Nieto, Juan and Siegwart, Roland and Nardi, Daniele and Pretto, Alberto}
}
@article {potena2019agricolmap,
	title = {AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming},
	journal = {IEEE Robotics and Automation Letters},
	volume = {4},
	number = {2},
	year = {2019},
	pages = {1085{\textendash}1092},
	publisher = {IEEE},
	author = {Potena, Ciro and Khanna, Raghav and Nieto, Juan and Siegwart, Roland and Nardi, Daniele and Pretto, Alberto}
}
@article {11573/1220042,
	title = {{AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming}},
	journal = {IEEE ROBOTICS AND AUTOMATION LETTERS},
	volume = {{4}},
	number = {{2}},
	year = {2019},
	pages = {1085-1092},
	keywords = {robotics in agriculture and forestry}, {multi-robot systems},
	doi = {{10.1109/LRA.2019.2894468}},
	author = {Potena, Ciro and Khanna, Raghav and Nieto, Juan and Siegwart, Roland and Nardi, Daniele and Pretto, Alberto}
}
@article {11573/1132076,
	title = {{Automatic model based dataset generation for fast and accurate crop and weeds detection}},
	volume = {{False}},
	number = {{False}},
	year = {2017},
	pages = {False-False},
	keywords = {Feature extraction, image classification, image segmentation, image texture, learning (artificial intelligence), Sugar industry, training, visualization}, {crops},
	doi = {{10.1109/IROS.2017.8206408}},
	author = {Di Cicco, Maurilio and Potena, Ciro and Grisetti, Giorgio and Pretto, Alberto}
}
@article {11573/1132076,
	title = {{Automatic model based dataset generation for fast and accurate crop and weeds detection}},
	volume = {{False}},
	number = {{False}},
	year = {2017},
	pages = {False-False},
	keywords = {Feature extraction, image classification, image segmentation, image texture, learning (artificial intelligence), Sugar industry, training, visualization}, {crops},
	doi = {{10.1109/IROS.2017.8206408}},
	author = {Di Cicco, Maurilio and Potena, Ciro and Grisetti, Giorgio and Pretto, Alberto}
}
@article {11573/1132076,
	title = {{Automatic model based dataset generation for fast and accurate crop and weeds detection}},
	volume = {{False}},
	number = {{False}},
	year = {2017},
	pages = {False-False},
	keywords = {Feature extraction, image classification, image segmentation, image texture, learning (artificial intelligence), Sugar industry, training, visualization}, {crops},
	doi = {{10.1109/IROS.2017.8206408}},
	author = {Di Cicco, Maurilio and Potena, Ciro and Grisetti, Giorgio and Pretto, Alberto}
}
@article {11573/1132076,
	title = {{Automatic model based dataset generation for fast and accurate crop and weeds detection}},
	volume = {{False}},
	number = {{False}},
	year = {2017},
	pages = {False-False},
	keywords = {Feature extraction, image classification, image segmentation, image texture, learning (artificial intelligence), Sugar industry, training, visualization}, {crops},
	doi = {{10.1109/IROS.2017.8206408}},
	author = {Di Cicco, Maurilio and Potena, Ciro and Grisetti, Giorgio and Pretto, Alberto}
}
