Biblio

Export 54 results:
Autor Título [ Tipo(Asc)] Año
Filters: First Letter Of Last Name is B  [Clear All Filters]
Thesis
Abraham L.  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.
Bromberg F, Margaritis D.  2007.  Markov networks structure discovery using independence tests. Computer Science. Doctor of Philosophy:182.
Schlüter F, Bromberg F.  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.
Journal Article
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.
Diedrichs ALaura, Bromberg F, Dujovne D, Brun-Laguna K, Watteyne T.  2018.  Prediction of frost events using machine learning and IoT sensing devices. IEEE Internet of Things Journal. 5(6):4589-4597.
Diedrichs ALaura, Bromberg F, Dujovne D, Brun-Laguna K, Watteyne T.  2018.  Prediction of frost events using machine learning and IoT sensing devices. IEEE Internet of Things Journal. 5(6):4589-4597.
Watteyne T, Diedrichs ALaura, Brun-Laguna K, Chaar JEmilio, Dujovne D, Taffernaberry JCarlos, Mercado G.  2016.  Peach: Predicting frost events in peach orchards using iot technology. EAI Endorsed Transactions on the Internet of Things. (5)
Edera A, Schlüter F, Bromberg F.  2014.  Learning Markov networks networks with context-specific independences.. International Journal on Artificial Intelligence Tools. 23(06)
Bromberg F, Margaritis D.  2009.  Improving the reliability of causal discovery from small data sets using argumentation. The Journal of Machine Learning Research. 10:301–340.
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.
Schlüter F, Bromberg F, Edera A.  2014.  The IBMAP approach for Markov network structure learning. Annals of Mathematics and Artificial Intelligence. 72(3):197--223.
Berdún L, Bromberg F.  2009.  Guest Editorial: 10th Argentinean Symposium on Artificial Intelligence (ASAI 2009). Inteligencia Artificial.. 13(44):4.
Berdún L, Bromberg F.  2009.  Guest Editorial: 10th Argentinean Symposium on Artificial Intelligence (ASAI 2009). Inteligencia Artificial.. 13(44):4.
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.
Abraham L, Bromberg F, Forradellas R.  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.
Bromberg F, Margaritis D, Honavar V.  2009.  Efficient Markov network structure discovery using independence tests. Journal of Artificial Intelligence Research. 35:449–484.
Margaritis D, Bromberg F.  2009.  Efficient Markov network discovery using particle filters. Computational Intelligence. 25(4):367–394.
Schlüter F, Strappa Y, Bromberg F, Milone DH.  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
Catania CA, Bromberg F, Garino CGarcía.  2012.  An autonomous labeling approach to support vector machines algorithms for network traffic anomaly detection. Expert Systems with Applications. 39:1822–1829.

Páginas