Biblio
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Autor Título [ Tipo
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2006. Efficient Markov network structure discovery using independence tests. Proceedings of the SIAM Conference in Data Mining. :141--152.
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2014. Estimación de carga muscular mediante imágenes. Argentinean Symposium of Artificial Intelligence (ASAI) - Jornadas Argentinas de Informática. :91--98.
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2008. Learning Markov Network Structure using Few Independence Tests.. SIAM Data Mining. :680--691.
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2021. Multi species weed detection with Retinanet one-step network in a maize field. Precision agriculture’21. :2223–2228.
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2012. An autonomous labeling approach to support vector machines algorithms for network traffic anomaly detection. Expert Systems with Applications. 39:1822–1829.
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2017. Blankets Joint Posterior score for learning Markov network structures . International Journal of Approximate Reasoning. https://doi.org/10.1016/j.ijar.2017.10.018
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2009. Efficient Markov network discovery using particle filters. Computational Intelligence. 25(4):367–394.
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2009. Efficient Markov network structure discovery using independence tests. Journal of Artificial Intelligence Research. 35:449–484.
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2018. Ensemble of shape functions and support vector machines for the estimation of discrete arm muscle activation from external biceps 3D point clouds. Computers in Biology and Medicine. 95:129-139.
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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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2009. Guest Editorial: 10th Argentinean Symposium on Artificial Intelligence (ASAI 2009). Inteligencia Artificial.. 13(44):4.
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2009. Guest Editorial: 10th Argentinean Symposium on Artificial Intelligence (ASAI 2009). Inteligencia Artificial.. 13(44):4.
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2014. The IBMAP approach for Markov network structure learning. Annals of Mathematics and Artificial Intelligence. 72(3):197--223.
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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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2009. Improving the reliability of causal discovery from small data sets using argumentation. The Journal of Machine Learning Research. 10:301–340.
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2014. Learning Markov networks networks with context-specific independences.. International Journal on Artificial Intelligence Tools. 23(06)
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2016. Peach: Predicting frost events in peach orchards using iot technology. EAI Endorsed Transactions on the Internet of Things. (5)
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2018. Prediction of frost events using machine learning and IoT sensing devices. IEEE Internet of Things Journal. 5(6):4589-4597.
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2018. Prediction of frost events using machine learning and IoT sensing devices. IEEE Internet of Things Journal. 5(6):4589-4597.
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2021. Towards practical 2D grapevine bud detection with fully convolutional networks. Computers and Electronics in Agriculture. 182:105947.
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2014. El enfoque IBMAP para aprendizaje de estructuras de redes de Markov. Tesis doctoral en Facultad de Ciencias Exactas - Universidad Nacional del Centro de la Provincia de Buenos Aires. Director: Facundo Bromberg. . Doctorado en Ciencias de la Computación (PhD in Computer Science):138.
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2007. Markov networks structure discovery using independence tests. Computer Science. Doctor of Philosophy:182.
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2018. Visión computacional y aprendizaje de máquinas aplicado a la estimación de activación muscular del bíceps braquial. Universidad Nacional del Centro de la Provincia de Buenos Aires - Facultad de Ciencias Exactas. Computer Science Ph.D:63.