Biblio

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Marset WVillegas, Perez DSebastian, Díaz CAriel, Bromberg F.  2021.  Towards practical 2D grapevine bud detection with fully convolutional networks. Computers and Electronics in Agriculture. 182:105947.
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Schlüter F, Bromberg F, Pérez DS.  2010.  Speeding up the execution of a large number of statistical tests of independence. Proceedings of ASAI 2010, Argentinean Symposioum of Artificial Intelligence.
Grünwaldt G, Pecchia M, Diedrichs ALaura, Tabacchi G, Mercado G.  2015.  Sonda de temperatura para uso agrícola. CASE Congreso Argentino de Sistemas Embebidos.
Pérez DS, Bromberg F.  2012.  Segmentación de imágenes en viñedos para la medición autónoma de variables vitícolas. XVIII Congreso Argentino de Ciencias de la Computación.
Perez C, Diedrichs ALaura.  2016.  SDCP: Streaming Distributed Control Protocol.
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Correa JMLópez, Todeschini M, Pérez DS, Karouta J, Bromberg F, Ribeiro A, Andújar D.  2021.  Multi species weed detection with Retinanet one-step network in a maize field. Precision agriculture’21. :2223–2228.
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Diedrichs ALaura, Tabacchi G, Grunwaldt G, Pecchia M, Mercado G, Antivilo FGonzalez.  2014.  Low-power wireless sensor network for frost monitoring in agriculture research. Biennial Congress of Argentina (ARGENCON), 2014 IEEE.
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Bromberg F, Pérez DS.  2012.  Interpolación Espacial Mediante Aprendizaje de Máquinas en Viñedos de la Provincia de Mendoza, Argentina.. 13th Argentine Symposium on Artificial Intelligence.
Pérez DSebastián, Bromberg F, Diaz CAriel.  2017.  Image classification for detection of winter grapevine buds in natural conditions using scale-invariant features transform, bag of features and support vector machines. Computers and Electronics in Agriculture. 135:81-95.
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Diaz CAriel, Pérez DSebastián, Miatello H, Bromberg F.  2018.  Grapevine buds detection and localization in 3D space based on Structure from Motion and 2D image classification. Computers in Industry. 99C (Special Issue on Machine Vision for Outdoor Environments):303-312.
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Perez DSebastian.  2017.  Diseño de Algoritmos de Aprendizajes de Máquinas y Visión Computacional para la Medición Autónoma de Variables Vitı́colas.
Marset WVillegas, Pérez DS, Díaz CA, Bromberg F.  2020.  Deep Learning for 2D Grapevine Bud Detection.
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Prince SJD.  2012.  Computer vision: models, learning, and inference.
Pérez DSebastián, Bromberg F, Gonzalez-Antivilo F.  2016.  Computer Vision Approach for Low Cost, High Precision Measurement of Grapevine Trunk Diameter in Outdoor Conditions.
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Paproki A, Fripp J, Salvado O, Sirault X, Berry S, Furbank R.  2011.  Automated 3D segmentation and analysis of cotton plants. Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on.