INVESTIGADORES
BROMBERG facundo
artículos
VILLEGAS MARSET, WENCESLAO; PEREZ, DIEGO SEBASTIÁN; DIAZ, CARLOS ARIEL; BROMBERG, FACUNDO
Towards practical 2D grapevine bud detection with fully convolutional networks
COMPUTERS AND ELETRONICS IN AGRICULTURE; Lugar: Amsterdam; Año: 2021 vol. 182
DIEDRICHS, ANA LAURA; BROMBERG, FACUNDO; DUJOVNE, DIEGO; BRUN-LAGUNA, KEOMA; WATTEYNE, THOMAS
Prediction of frost events using machine learning and IoT sensing devices
IEEE Internet of Things Journal; Lugar: New York; Año: 2018
DÍAZ, CARLOS ARIEL; PÉREZ, DIEGO SEBASTIÁN; MIATELLO, HUMBERTO; BROMBERG, FACUNDO
Grapevine buds detection and localization in 3D space based on Structure from Motion and 2D image classification
COMPUTERS IN INDUSTRY; Año: 2018 vol. 99 p. 303 - 312
SCHLÜTER, FEDERICO; STRAPPA, YANELA; MILONE, DIEGO H.; BROMBERG, FACUNDO
Blankets Joint Posterior score for learning Markov network structures
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; Año: 2018 vol. 92 p. 295 - 320
ABRAHAM, LEANDRO; BROMBERG, FACUNDO; FORRADELLAS, RAYMUNDO
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; Año: 2018
PÉREZ, DIEGO SEBASTIÁN; BROMBERG, FACUNDO; DIAZ, CARLOS ARIEL
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 ELETRONICS IN AGRICULTURE; Año: 2017 vol. 135 p. 81 - 95
SCHLÜTER, FEDERICO; BROMBERG, FACUNDO; EDERA, ALEJANDRO
The IBMAP approach for Markov network structure learning
ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE; Lugar: Berlin; Año: 2014
EDERA, ALEJANDRO; SCHLÜTER, FEDERICO; BROMBERG, FACUNDO
Learning Markov networks with context- specific independences
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS; Lugar: London, UK; Año: 2014 vol. 23
CATANIA, CARLOS A.; BROMBERG, FACUNDO; GARCIA GARINO, CARLOS
An autonomous labeling approach to SVM algorithms for network traffic anomaly detection.
EXPERT SYSTEMS WITH APPLICATIONS; Lugar: Amsterdam; Año: 2012 vol. 39 p. 1822 - 1829
FACUNDO BROMBERG; DIMITRIS MARGARITIS
Improving the Reliability of Causal Discovery from Small Data Sets using Argumentation
JOURNAL OF MACHINE LEARNING RESEARCH; Lugar: online; Año: 2009 vol. 10 p. 301 - 340
BROMBERG, FACUNDO; MARGARITIS, DIMITRIS; HONAVAR, VASANT
Efficient Markov Network Structure Discovery using Independence Tests
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, THE; Lugar: online; Año: 2009 vol. 35 p. 449 - 485
MARGARITIS, DIMITRIS; BROMBERG, FACUNDO
Efficient Markov Network Discovery Using Particle Filters
COMPUTATIONAL INTELLIGENCE; Lugar: Edmonton, Alberta, CANADA; Año: 2009 vol. 25 p. 367 - 394
BERDÚN, LUIS; BROMBERG, FACUNDO
Guest Editorial: 10 Argentinean Symposium on Artificial Intelligence (ASAI 2009)
REVISTA IBEROAMERICANA DE INTELIGENCIA ARTIFICIAL; Año: 2009 vol. 13 p. 3 - 4