Biblio
Export 18 results:
Autor Título Tipo [ Año] Filters: First Letter Of Last Name is M [Clear All Filters]
Efficient Markov network structure discovery using independence tests. Proceedings of the SIAM Conference in Data Mining. :141--152.
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2006. Efficient and Robust Independence-Based Markov Network Structure Discovery.. 20th International Joint Conference of Artificial Inteliigence (IJCAI). :2431-2436.
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2007. Markov networks structure discovery using independence tests. Computer Science. Doctor of Philosophy:182.
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2007. Learning Markov Network Structure using Few Independence Tests.. SIAM Data Mining. :680--691.
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2008. 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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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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2009. RED SIPIA: Red de Sensores Inalámbricos para Investigación Agronómica. XIII Workshop de Investigadores en Ciencias de la Computación.
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2011. Aplicaciones de Internet de las Cosas SIPIA6-Red de Sensores Inalámbricos con IPv6. XV Workshop de Investigadores en Ciencias de la Computación.
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2013. Characterization of LQI behavior in WSN for glacier area in Patagonia Argentina. Embedded Systems (SASE/CASE), 2013 Fourth Argentine Symposium and Conference on. :1--6.
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2013. Low-power wireless sensor network for frost monitoring in agriculture research. Biennial Congress of Argentina (ARGENCON), 2014 IEEE.
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2014. Sonda de temperatura para uso agrícola. CASE Congreso Argentino de Sistemas Embebidos.
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2015. A demo of the PEACH IoT-based frost event prediction system for precision agriculture. Sensing, Communication, and Networking (SECON), 2016 13th Annual IEEE International Conference on.
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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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2016. 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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2017. 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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2018. Towards practical 2D grapevine bud detection with fully convolutional networks. Computers and Electronics in Agriculture. 182:105947.
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2021.