Publications

JOURNALS

1.  R.J. Murphy and S.T. Monteiro, Mapping the distribution of ferric iron minerals on a vertical mine face using derivative analysis of hyperspectral imagery (430–970 nm), ISPRS Journal of Photogrammetry & Remote Sensing, v. 75, pp. 29-39, 2013.
   [PDF] [BibTex]

@ARTICLE{Murphy_JISPRS_2013,
author={R.J. Murphy and Sildomar T. Monteiro},
journal={ISPRS Journal of Photogrammetry & Remote Sensing},
title={Mapping the distribution of ferric iron minerals on a vertical mine face using derivative analysis of hyperspectral imagery (430–970 nm)},
year={2013},
volume={75},
pages={29-39},
doi={10.1016/j.isprsjprs.2012.09.014},
keywords={Mapping, Hyperspectral, Derivative analysis, Mining, Iron ore}}



2.  R.J. Murphy, S.T. Monteiro, S. Schneider, Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors, IEEE Transactions on Geoscience and Remote Sensing, v. 50, n. 8, pp. 3066-3080, 2012.
   [PDF] [BibTex]

@ARTICLE{Monteiro_TGRS_2011,
author={R.J. Murphy and Sildomar T. Monteiro and S. Schneider},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors},
year={2012},
volume={50},
number={8},
pages={3066-3080},
doi={10.1109/TGRS.2011.2178419},
keywords={Geology, hyperspectral imaging, minerals, mining industry, spectral analysis, support vector machines}}



3. A. Kadkhodaie-Ilkhchi, S.T. Monteiro, F. Ramos and P. Hatherly, Rock Recognition from MWD data: A Comparative Study of Boosting, Neural Networks and Fuzzy Logic, IEEE Geoscience and Remote Sensing Letters, v.7, n. 4, pp. 680-684, 2010.
   [PDF] [BibTex]

@ARTICLE{Monteiro_GRSL_2010,
author={Kadkhodaie-Ilkhchi, A. and Sildomar T. Monteiro and Ramos, F. and Hatherly, P.},
journal={IEEE Geoscience and Remote Sensing Letters},
title={Rock Recognition From MWD Data: A Comparative Study of Boosting, Neural Networks, and Fuzzy Logic},
year={2010},
month=oct. ,
volume={7},
number={4},
pages={680 -684},
doi={10.1109/LGRS.2010.2046312},
keywords={geological modeling, measurement-while-drilling sensors, boosting, neural networks, pattern recognition}}



4. T. Edanaga, Y. Minekawa, S.T. Monteiro and Y. Kosugi, Studies on human skin extraction from hyperspectral data using particle swarm optimization, Journal of the Japan Society of Photogrammetry and Remote Sensing, v. 47, n. 3, pp. 23-36, 2008.
   [PDF] [BibTex]

@article{Edanaga_JJSPRS_2008,
title={Studies on human skin extraction from hyperspectral data using particle swarm optimization},
author={Edanaga, T. and Minekawa, Y. and Sildomar T. Monteiro and Kosugi, Y.},
journal={Journal of the Japan Society of Photogrammetry and Remote Sensing},
volume={47},
number={3},
pages={23--36},
year={2008},
keywords={particle swarm optimization, hyperspectral imaging, human skin}}



5. S.T. Monteiro and Y. Kosugi, Particle Swarms for Feature Extraction of Hyperspectral Data, IEICE Transactions on Information and Systems, v. E90-D, n. 7, pp. 1038-1046, 2007.
   [PDF] [BibTex] [Matlab code]

@article{Monteiro_IEICETrans_2007,
title={Particle swarms for feature extraction of hyperspectral data},
author={Sildomar T. Monteiro and Kosugi, Y.},
journal={IEICE Transactions on Information and Systems},
volume = {E90-D},
number={7},
pages={1038--1046},
issn={0916-8532},
year={2007},
doi = {10.1093/ietisy/e90-d.7.1038},
publisher = {Oxford University Press}
keywords = {feature extraction, hyperspectral data, neural networks, particle swarm optimization, principal components analysis}}



6. S.T. Monteiro, Y. Minekawa, Y. Kosugi, T. Akazawa, and K. Oda, Prediction of Sweetness and Amino Acid Content in Soybean Crops from Hyperspectral Imagery, ISPRS Journal of Photogrammetry & Remote Sensing, v. 62, n. 1, pp. 2-12, 2007.
   [PDF] [BibTex]

@article{Monteiro_JISPRS_2007,
title={Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery},
author={Sildomar T. Monteiro and Minekawa, Y. and Kosugi, Y. and Akazawa, T. and Oda, K.},
journal={ISPRS Journal of Photogrammetry and Remote Sensing},
volume={62},
number={1},
pages={2--12},
issn={0924-2716},
year={2007},
publisher={Elsevier},
doi = {10.1016/j.isprsjprs.2006.12.002},
keywords = {Agriculture, Hyperspectral image, Modeling, Neural networks, Spatial prediction}}



7. S.T. Monteiro, K. Uto, Y. Kosugi, N. Kobayashi, and E. Watanabe, Optimization of Infrared Spectral Manipulation for Surgical Visual Aid, Journal of Japan Society of Computer Aided Surgery, v. 8, n. 1, pp. 33-38, 2006.
   [PDF] [BibTex]

@article{Monteiro_JJSCAS_2006,
title={Optimization of infrared spectral manipulation for surgical visual aid},
author={Sildomar T. Monteiro and Uto, K. and Kosugi, Y. and Kobayashi, N. and Watanabe, E.},
journal={Journal of Japan Society of Computer Aided Surgery},
volume={8},
number={1},
pages={33--38},
year={2006},
keywords = {Image-guided surgery, Infrared medical imaging, Hyperspectral imagery, Neural networks, Spectral manipulation}}



8. S.T. Monteiro, K. Uto, Y. Kosugi, N. Kobayashi, E. Watanabe, and K. Kameyama, Feature Extraction of Hyperspectral Data for under Spilled Blood Visualization Using Particle Swarm Optimization, International Journal of Bioelectromagnetism, v. 7, n. 1, pp. 232-235, 2005.
   [PDF] [BibTex]

@article{Monteiro_IJBEM_2005,
title={Feature extraction of hyperspectral data for under spilled blood visualization using particle swarm optimization},
author={Sildomar T. Monteiro and Uto, K. and Kosugi, Y. and Kobayashi, N. and Watanabe, E. and Kameyama, K.},
journal={International Journal of Bioelectromagnetism},
volume={7},
number={1},
pages={232--235},
year={2005},
Keywords={Biomedical imaging, feature extraction, hyperspectral imagery, particle swarm optimization}}



9. S.T. Monteiro and C. H. C. Ribeiro,Performance of reinforcement learning algorithms in mobile robotics under conditions of sensorial ambiguity, Journal of Control and Automation of the Brazilian Society of Automatics, v. 15, n. 3, pp. 320-338, 2004. [in Portuguese]
   [PDF] [BibTex]

@article{Monteiro_SBA-CA_2004,
title = {Desempenho de algoritmos de aprendizagem por reforco sob condicoes de ambiguidade sensorial em robotica movel},
journal = {{SBA} Controle & Automacao},
author={Sildomar T. Monteiro and Ribeiro, Carlos H. C.},
volume = {15},
year = {2004},
pages = {320--338},
ISSN = {0103-1759},
publisher = {scielo},
doi = {10.1590/S0103-17592004000300008},
keywords={reinforcement learning, mapping, navigation, mobile robots}}

CONFERENCES

10.  H. Zhou, P. Hatherly, S.T. Monteiro, F. Ramos, F. Oppolzer, E. Nettleton and S. Scheding, Automatic rock recognition from drilling performance data, IEEE Intl. Conf. on Robotics and Automation (ICRA), pp. 3407-3412, Saint Paul, USA, 2012.
    [PDF] [BibTex]

@INPROCEEDINGS{Zhou_ICRA_2012,
author={H. Zhou and P. Hatherly and S.T. Monteiro and F. Ramos and F. Oppolzer and E. Nettleton and S. Scheding},
booktitle={IEEE International Conference on Robotics and Automation},
title={Automatic Rock Recognition from Drilling Performance Data},
year={2012},
pages={3407-3412},
keywords={Gaussian processes, regression, clustering, pattern recognition, geology},
doi={10.1109/ICRA.2012.6224745}}



11. S.T. Monteiro, J. van de Ven, F. Ramos and P. Hatherly, Learning 3D Geological Structure from Drill-Rig Sensors for Automated Mining, International Joint Conference on Artificial Intelligence (IJCAI), pp. 2500-2506, Barcelona, Spain, 2011. (17% acceptance rate)
    [PDF] [BibTex] [Video]

@INPROCEEDINGS{MonteiroIJCAI2011,
author={Sildomar T. Monteiro and J. van de Ven and F. Ramos and P. Hatherly},
booktitle={International Joint Conference on Artificial Intelligence},
title={Learning 3D Geological Structure from Drill-Rig Sensors for Automated Mining},
pages={2500--2506},
year={2011},
doi={10.5591/978-1-57735-516-8/IJCAI11-416},
keywords={conditional random fields, inference algorithms, 3D modeling, boosting, multi-sensor data fusion}}


12. A.S.J. Tjiong and S.T. Monteiro, Feature selection with PSO and kernel methods for hyperspectral classification, IEEE Congress on Evolutionary Computation (CEC), pp. 1762-1769, New Orleans, USA, 2011.
    [PDF] [BibTex] [Matlab code]

@INPROCEEDINGS{TjiongCEC2011,
author={A.S.J. Tjiong and Sildomar T. Monteiro},
booktitle={IEEE Congress on Evolutionary Computation},
title={Feature selection with PSO and kernel methods for hyperspectral classification},
pages={1762--1769},
year={2011},
doi={10.1109/CEC.2011.5949828},
keywords={support vector machines, particle swarm optimization, observation angle dependent kernel}}


13. S.T. Monteiro and R.J. Murphy, Embedded feature selection of hyperspectral bands with boosted decision trees, IEEE Intl. Geoscience and Remote Sensing Symposium (IGARSS), pp. 2361-2364, Vancouver, Canada, 2011.
    [PDF] [BibTex] [Video] [Slides]

@INPROCEEDINGS{MonteiroIGARSS2011,
author={Sildomar T. Monteiro and R.J. Murphy},
booktitle={IEEE International Geoscience and Remote Sensing Symposium},
title={Embedded feature selection of hyperspectral bands with boosted decision trees},
pages={2361--2364},
year={2011},
doi={10.1109/IGARSS.2011.6049684},
keywords={feature extraction, boosting, decision trees, hyperspectral data}}


14. H. Zhou, S.T. Monteiro, P. Hatherly, F. Ramos, E. Nettleton and F. Oppolzer, Automated rock recognition with wavelet feature space projection and Gaussian process classification, IEEE Intl. Conf. on Robotics and Automation (ICRA), pp. 4444-4450, Alaska, USA, 2010.
    [PDF] [BibTex]

@INPROCEEDINGS{Zhou2010ICRAAutomatedRock,
author={Hang Zhou and Sildomar T. Monteiro and Hatherly, P. and Ramos, F. and Nettleton, E. and Oppolzer, F.},
booktitle={IEEE International Conference on Robotics and Automation},
title={Automated rock recognition with wavelet feature space projection and Gaussian Process classification},
year={2010},
pages={4444--4450},
keywords={Gaussian process classification, automated rock recognition, wavelet feature extraction, image classification},
doi={10.1109/ROBOT.2010.5509605},
ISSN={1050-4729}}



15. S.T. Monteiro and R.J. Murphy, Calibrating probabilities for hyperspectral classification of rock types, IEEE Intl. Geoscience and Remote Sensing Symposium (IGARSS), pp. 2800-2803, Honolulu, USA, 2010.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_IGARSS_2010,
author={Sildomar T. Monteiro and Murphy, R.J.},
booktitle={IEEE International Geoscience and Remote Sensing Symposium},
title={Calibrating probabilities for hyperspectral classification of rock types},
year={2010},
pages={2800--2803},
keywords={boosted decision trees, calibrating probability, hyperspectral classification, support vector machines, geophysical signal processing},
doi={10.1109/IGARSS.2010.5649482},
ISSN={2153-6996}}



16. J. Nieto, D. Viejo and S.T. Monteiro, 3D geological modelling using laser and hyperspectral data, IEEE Intl. Geoscience and Remote Sensing Symposium (IGARSS), pp. 4568-4571, Honolulu, USA, 2010.
    [PDF] [BibTex]

@INPROCEEDINGS{Nieto_IGARSS_2010,
author={Nieto, J.I. and Sildomar T. Monteiro and Viejo, D.},
booktitle={IEEE International Geoscience and Remote Sensing Symposium},
title={3D geological modelling using laser and hyperspectral data},
year={2010},
pages={4568--4571},
keywords={3D geological modelling, hyperspectral images, laser data, mobile robotic platform, registration algorithms, image classification},
doi={10.1109/IGARSS.2010.5651553},
ISSN={2153-6996}}



17. S.T. Monteiro, F. Ramos, P. Hatherly, Conditional random fields for rock characterization using drill measurements, International Conference on Machine Learning and Applications (ICMLA), pp. 366-371, Miami, USA, 2009.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_ICMLA_2009,
author={Sildomar T. Monteiro and Ramos, F. and Hatherly, P.},
booktitle={International Conference on Machine Learning and Applications},
title={Conditional Random Fields for Rock Characterization Using Drill Measurements},
year={2009},
pages={366--371},
keywords={belief propagation, boosting algorithm, conditional random fields, measurement-while-drilling, autonomous drill rig},
doi={10.1109/ICMLA.2009.80}}



18. S.T. Monteiro, R.J. Murphy, F. Ramos and J. Nieto, Applying boosting for hyperspectral classification of ore-bearing rocks, IEEE Intl. Workshop on Machine Learning for Signal Processing (MLSP), Grenoble, France, 2009.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_MLSP_2009,
author={Sildomar T. Monteiro and Murphy, R.J. and Ramos, F. and Nieto, J.},
booktitle={IEEE International Workshop on Machine Learning for Signal Processing},
title={Applying boosting for hyperspectral classification of ore-bearing rocks},
year={2009},
pages={1--6},
keywords={GentleBoost, LogitBoost, Savitzky-Golay, derivative analysis, hyperspectral classification, support vector machine},
doi={10.1109/MLSP.2009.5306219}}



19. S. Schneider, R.J. Murphy, S.T. Monteiro and E. Nettleton, On the development of a hyperspectral library for autonomous mining systems, Australasian Conference on Robotics and Automation (ACRA), Sydney, Australia, 2009.
    [PDF] [BibTex]

@INPROCEEDINGS{Schneider2009,
author = {Schneider, S. and Murphy, R. and Sildomar T. Monteiro and Nettleton, E. W.},
title = {On the development of a hyperspectral library for autonomous mining},
booktitle = {Australasian Conference on Robotics and Automation},
year = {2009}}



20. H. Zhou, S.T. Monteiro, P. Hatherly, F. Ramos, E. Nettleton and F. Oppolzer, Spectral feature selection for automated rock recognition using gaussian process classification, Australasian Conference on Robotics and Automation (ACRA), Sydney, Australia, 2009.
    [PDF] [BibTex]

@INPROCEEDINGS{zhou2009,
title={Spectral Feature Selection for Automated Rock Recognition Using Gaussian Process Classification},
author={Zhou, H. and Sildomar T. Monteiro and Hatherly, P. and Ramos, F. and Nettleton, E. and Oppolzer, F.},
booktitle={Proceedings of Australasian Conference on Robotics and Automation},
year={2009}}



21. S.T. Monteiro, K. Uto, Y. Kosugi, K. Oda, Y. Iino and G. Saito, Hyperspectral image classification of grass species in northeast Japan, IEEE Intl. Geoscience and Remote Sensing Symposium (IGARSS), vol. 4, pp. 399-402, Boston, 2008.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_IGARSS_2008,
author={Sildomar T. Monteiro and Uto, K. and Kosugi, Y. and Oda, K. and Iino, Y. and Saito, G.},
booktitle={IEEE International Geoscience and Remote Sensing Symposium},
title={Hyperspectral Image Classification of Grass Species in Northeast Japan},
year={2008},
volume={4},
pages={399-402},
keywords={artificial neural networks, hyperspectral image classification, geophysical signal processing},
doi={10.1109/IGARSS.2008.4779742}}



22. Y. Kosugi, D. Gullaume, Y. Takabayashi, S.T. Monteiro, M. Yamaki, K. Uto and G. Saito, Low-altitude hyperspectral imaging of Naruko integrated field for the interpretation of high-altitude observations, 6th  Intl. Symposium on Integrated Field Science, p.A-2, Sendai, Japan, 2008.
    [PDF] [BibTex]

@INPROCEEDINGS{Kosugi2008,
title={Low-Altitude Hyperspectral Imaging of {Naruko} Integrated Field for the Interpretation of High-Altitude Observations},
author={Kosugi, Y. and Guillaume, D. and Takabayashi, Y. and Sildomar T. Monteiro and Yamaki, M. and Uto, K. and Saito, G.},
booktitle={6th International Symposium on Integrated Field Science},
volume={6},
pages={135-136},
year={2008}}



23. S.T. Monteiro and Y. Kosugi, A Particle Swarm Optimization-based Approach for Hyperspectral Band Selection, IEEE Congress on Evolutionary Computation (CEC), pp. 3335-3340, Singapore, 2007.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_CEC_2007,
author={Sildomar T. Monteiro and Kosugi, Y.},
booktitle={IEEE Congress on Evolutionary Computation},
title={A particle swarm optimization-based approach for hyperspectral band selection},
year={2007},
pages={3335--3340},
keywords={artificial neural networks, feature selection, hyperspectral band selection, particle swarm optimisation,
doi={10.1109/CEC.2007.4424902}}



24. S.T. Monteiro and Y. Kosugi, Applying particle swarm intelligence for feature selection of spectral imagery, 7th Intl. Conf. on Intelligent Systems Design and Applications (ISDA), pp. 933-938, Rio de Janeiro, Brazil, 2007.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_ISDA_2007,
author={Sildomar T. Monteiro and Kosugi, Y.},
booktitle={7th International Conference on Intelligent Systems Design and Applications},
title={Applying Particle Swarm Intelligence for Feature Selection of Spectral Imagery},
year={2007},
pages={933--938},
keywords={feature selection, neural networks, particle swarm optimization, spectral imagery, image processing},
doi={10.1109/ISDA.2007.95}}



25. S.T. Monteiro, Y. Minekawa, Y. Kosugi, T. Akazawa, and K. Oda, Prediction of Sweetness and Nitrogen Content in Soybean Crops from High Resolution Hyperspectral Imagery, IEEE Intl. Geoscience and Remote Sensing Symposium (IGARSS), vol. 5, pp. 2263-2266, Denver, USA, 2006.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_IGARSS_2006,
author={Sildomar T. Monteiro and Minekawa, Y. and Kosugi, Y. and Akazawa, T. and Oda, K.},
booktitle={IEEE International Geoscience and Remote Sensing Symposium},
title={Prediction of Sweetness and Nitrogen Content in Soybean Crops from High Resolution Hyperspectral Imagery},
year={2006},
pages={2263--2266},
keywords={derivative analysis, hyperspectral imagery, neural network regression, geophysical signal processing},
doi={10.1109/IGARSS.2006.585}}



26. S.T. Monteiro, Y. Minekawa, Y. Kosugi, T. Akazawa, and K. Oda, High Resolution Hyperspectral Imagery for Estimating Sweetness Content in Soybean Crops, Institute of Electronics, Information and Communication Engineers General Conference (IEICE), BS-6-13, SE-24, Tokyo, Japan, 2006.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_IEICE_2006,
title={High Resolution Hyperspectral Imagery for Estimating Sweetness Content in Soybean Crops},
author={Sildomar T. Monteiro and Minekawa, Y. and Kosugi, Y. and Akazawa, T. and Oda, K.},
booktitle={Proceedings of the IEICE General Conference},
volume={BS-6-13},
number={SE-24},
year={2006},
issn={1349-1369}}



27. S.T. Monteiro, H. Nakamoto, H. Ogawa, and N. Matsuhira, Robust mobile robot map building using sonar and vision, JSME Conference on Robotics and Mechatronics (ROBOMEC), 2P1-N-052, pp. 1-4, Kobe, Japan, 2005.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_ROBOMEC_2005,
title={Robust mobile robot map building using sonar and vision},
author={Sildomar T. Monteiro and Nakamoto, H. and Ogawa, H. and Matsuhira, N.},
booktitle={JSME Conference on Robotics and Mechatronics},
volume={2P1-N-052},
pages={1--4},
year={2005}}



28. S.T. Monteiro, K. Uto, Y. Kosugi, and E. Watanabe, Towards Applying hyperspectral Imagery as an Intraoperative Visual Aid Tool, 4th IASTED Intl. Conf. on Visualization, Imaging and Image Processing (VIIP), pp.483-488, Marbella, Spain, 2004.
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_VIIP_2004,
title={Towards Applying hyperspectral Imagery as an Intraoperative Visual Aid Tool},
author={Sildomar T. Monteiro and Kosugi, Y. and Uto, K. and Watanabe, E.},
booktitle={4th IASTED International Conference on Visualization, Imaging and Image Processing},
pages={483--488},
year={2004}}



29. S.T. Monteiro and C.H.C. Ribeiro, Learning of mobile robot navigation based on autonomously acquired maps, XXIII Brazilian Computer Society Conference (SBC), v. 1, pp. 152-162, Campinas, Brazil, 2003. [in Portuguese]
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_ENIA_2003,
title={Aprendizagem da Navegacao em Robos Moveis a Partir de Mapas Obtidos Autonomamente},
author={Sildomar T. Monteiro and Ribeiro, C.H.C.},
booktitle={Anais do XXIII Congresso da Sociedade Brasileira de Computacao},
volume={1},
pages={152--162},
year={2003}}



30. S.T. Monteiro and C.H.C. Ribeiro, Acquisition of cognitive maps for the Magellan Pro mobile robot, XIV Brazilian Automation Conference (CBA), pp.1543-1548, Natal, Brazil, 2002. [in Portuguese]
    [PDF] [BibTex]

@INPROCEEDINGS{Monteiro_CBA_2002,
title={Obtencao de Mapas Cognitivos para o Robo Magellan Pro},
author={Sildomar T. Monteiro and Ribeiro, C.H.C.},
booktitle={Anais do XIV Congresso Brasileiro de Automatica},
pages={1543--1548},
year={2002}}

WORKSHOPS

30. S.T. Monteiro, F. Ramos, P. Hatherly, Learning CRF models from drill rig sensors for autonomous mining, NIPS Workshop: Learning from Multiple Sources with Applications to Robotics, Whistler, Canada, 2009. (oral)
    [PDF] [Video]
31. S.T. Monteiro, K. Uto, Y. Kosugi, and E. Watanabe, Towards a Surgical Tool Using Hyperspectral Imagery as Visual Aid, MICCAI Workshop: Augmented Environments for Medical Imaging and Computer-aided Surgery (AMI-ARCS), pp.97-103, Rennes, France, 2004. (oral)
    [PDF]

OTHER

32. S.T. Monteiro, Automatic Hyperspectral Data Analysis: A machine learning approach to high dimensional feature extraction, Saarbrucken, Germany: VDM Verlag, 2010.
    [Amazon] [BibTex]

@BOOK{Monteiro2010b,
author = {Sildomar T. Monteiro},
title = {Automatic Hyperspectral Data Analysis: A machine learning approach to high dimensional feature extraction},
publisher = {VDM Verlag},
address = {Saarbrucken, Germany},
year = {2010}}



33. F.T. Ramos, S.T. Monteiro, P.J. Hatherly, “Iron Ore Rock Recognition Trials,”Technical Report: ACFR-TR-2009-001, University of Sydney, 2008.
    [PDF] [BibTex]

@TECHREPORT{Ramos2008,
author = {Ramos, F. and Hatherly, P. and Sildomar T. Monteiro},
title = {Iron Ore Rock Recognition Trials},
institution = {Australian Centre for Field Robotics},
pages={1--41},
year = {2008}}

1. Y. Kosugi, S.T. Monteiro, K. Uto, and E. Watanabe, “Means and equipments for surgical viewing aid,” US patent application 2004/604,743. Japan Patent 2006-085688.