David Cox - Publications

Affiliations: 
Rowland Institute, Harvard, Cambridge, MA, United States 
Area:
Object recognition
Website:
http://www.rowland.harvard.edu/rjf/cox/index.html

44 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2018 Fong RC, Scheirer WJ, Cox DD. Using human brain activity to guide machine learning. Scientific Reports. 8: 5397. PMID 29599461 DOI: 10.1038/s41598-018-23618-6  0.76
2015 Zoccolan D, Cox DD, Benucci A. Editorial: What can simple brains teach us about how vision works. Frontiers in Neural Circuits. 9: 51. PMID 26483639 DOI: 10.3389/fncir.2015.00051  1
2015 Bergstra J, Komer B, Eliasmith C, Yamins D, Cox DD. Hyperopt: A Python library for model selection and hyperparameter optimization Computational Science and Discovery. 8. DOI: 10.1088/1749-4699/8/1/014008  1
2015 Bergstra J, Pinto N, Cox DD. SkData: Data sets and algorithm evaluation protocols in Python Computational Science and Discovery. 8. DOI: 10.1088/1749-4699/8/1/014007  1
2015 Papa JP, Rosa GH, Marana AN, Scheirer W, Cox DD. Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques Journal of Computational Science. 9: 14-18. DOI: 10.1016/j.jocs.2015.04.014  1
2015 Papa JP, Scheirer W, Cox DD. Fine-tuning Deep Belief Networks using Harmony Search Applied Soft Computing Journal. DOI: 10.1016/j.asoc.2015.08.043  1
2014 Scheirer WJ, Anthony SE, Nakayama K, Cox DD. Perceptual Annotation: Measuring Human Vision to Improve Computer Vision. Ieee Transactions On Pattern Analysis and Machine Intelligence. 36: 1679-86. PMID 26353347 DOI: 10.1109/TPAMI.2013.2297711  0.76
2014 Cox DD, Dean T. Neural networks and neuroscience-inspired computer vision. Current Biology : Cb. 24: R921-9. PMID 25247371 DOI: 10.1016/j.cub.2014.08.026  1
2014 Cox DD. Do we understand high-level vision? Current Opinion in Neurobiology. 25: 187-93. PMID 24552691 DOI: 10.1016/j.conb.2014.01.016  1
2014 Scheirer WJ, Anthony SE, Nakayama K, Cox DD. Perceptual annotation: Measuring human vision to improve computer vision Ieee Transactions On Pattern Analysis and Machine Intelligence. 36: 1679-1686. DOI: 10.1109/TPAMI.2013.2297711  1
2014 Chiachia G, Falcão AX, Pinto N, Rocha A, Cox D. Learning person-specific representations from faces in the wild Ieee Transactions On Information Forensics and Security. 9: 2089-2099. DOI: 10.1109/TIFS.2014.2359543  1
2014 Milford M, Scheirer W, Vig E, Glover A, Baumann O, Mattingley J, Cox D. Condition-invariant, Top-down visual place recognition Proceedings - Ieee International Conference On Robotics and Automation. 5571-5577. DOI: 10.1109/ICRA.2014.6907678  1
2014 Vig E, Dorr M, Cox D. Large-scale optimization of hierarchical features for saliency prediction in natural images Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2798-2805. DOI: 10.1109/CVPR.2014.358  1
2014 Milford M, Vig E, Scheirer W, Cox D. Vision-based simultaneous localization and mapping in changing outdoor environments Journal of Field Robotics. 31: 814-836. DOI: 10.1002/rob.21532  1
2013 Gunther M, Costa-Pazo A, Ding C, Boutellaa E, Chiachia G, Zhang H, De Assis Angeloni M, Struc V, Khoury E, Vazquez-Fernandez E, Tao D, Bengherabi M, Cox D, Kiranyaz S, De Freitas Pereira T, et al. The 2013 face recognition evaluation in mobile environment Proceedings - 2013 International Conference On Biometrics, Icb 2013. DOI: 10.1109/ICB.2013.6613024  1
2013 Milford M, Vig E, Scheirer W, Cox D. Towards condition-invariant, top-down visual place recognition Australasian Conference On Robotics and Automation, Acra 1
2013 Bergstra J, Yamins D, Cox DD. Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures 30th International Conference On Machine Learning, Icml 2013. 115-123.  1
2012 Chiachia G, Pinto N, Schwartz WR, Rocha A, Falcão AX, Cox D. Person-specific subspace analysis for unconstrained familiar face identification Bmvc 2012 - Electronic Proceedings of the British Machine Vision Conference 2012. DOI: 10.5244/C.26.101  1
2012 Bergstra J, Pinto N, Cox D. Machine learning for predictive auto-tuning with boosted regression trees 2012 Innovative Parallel Computing, Inpar 2012. DOI: 10.1109/InPar.2012.6339587  1
2012 Vig E, Dorr M, Cox DD. Saliency-based selection of sparse descriptors for action recognition Proceedings - International Conference On Image Processing, Icip. 1405-1408. DOI: 10.1109/ICIP.2012.6467132  1
2012 Pinto N, Cox DD. High-throughput-derived biologically-inspired features for unconstrained face recognition Image and Vision Computing. 30: 159-168. DOI: 10.1016/j.imavis.2011.12.009  1
2012 Pinto N, Cox DD. GPU Metaprogramming: A Case Study in Biologically Inspired Machine Vision Gpu Computing Gems Jade Edition. 457-471. DOI: 10.1016/B978-0-12-385963-1.00033-2  1
2012 Vig E, Dorr M, Cox D. Space-variant descriptor sampling for action recognition based on saliency and eye movements Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7578: 84-97. DOI: 10.1007/978-3-642-33786-4_7  1
2012 Pinto N, Cox D. An evaluation of the invariance properties of a biologically-inspired system for unconstrained face recognition Lecture Notes of the Institute For Computer Sciences, Social-Informatics and Telecommunications Engineering. 87: 505-518. DOI: 10.1007/978-3-642-32615-8_48  1
2011 Pinto N, Barhomi Y, Cox DD, DiCarlo JJ. Comparing state-of-the-art visual features on invariant object recognition tasks 2011 Ieee Workshop On Applications of Computer Vision, Wacv 2011. 463-470. DOI: 10.1109/WACV.2011.5711540  1
2011 Cox D, Pinto N. Beyond simple features: A large-scale feature search approach to unconstrained face recognition 2011 Ieee International Conference On Automatic Face and Gesture Recognition and Workshops, Fg 2011. 8-15. DOI: 10.1109/FG.2011.5771385  1
2011 Pinto N, Stone Z, Zickler T, Cox D. Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook Ieee Computer Society Conference On Computer Vision and Pattern Recognition Workshops. DOI: 10.1109/CVPRW.2011.5981788  1
2010 Zoccolan D, Graham BJ, Cox DD. A self-calibrating, camera-based eye tracker for the recording of rodent eye movements. Frontiers in Neuroscience. 4: 193. PMID 21152259 DOI: 10.3389/fnins.2010.00193  1
2010 Sriram V, Cox D, Tsoi KH, Luk W. Towards an embedded biologically-inspired machine vision processor Proceedings - 2010 International Conference On Field-Programmable Technology, Fpt'10. 273-278. DOI: 10.1109/FPT.2010.5681487  1
2009 Pinto N, Doukhan D, DiCarlo JJ, Cox DD. A high-throughput screening approach to discovering good forms of biologically inspired visual representation. Plos Computational Biology. 5: e1000579. PMID 19956750 DOI: 10.1371/journal.pcbi.1000579  1
2009 Mujica-Parodi LR, Strey HH, Frederick B, Savoy R, Cox D, Botanov Y, Tolkunov D, Rubin D, Weber J. Chemosensory cues to conspecific emotional stress activate amygdala in humans. Plos One. 4: e6415. PMID 19641623 DOI: 10.1371/journal.pone.0006415  1
2009 Li N, Cox DD, Zoccolan D, DiCarlo JJ. What response properties do individual neurons need to underlie position and clutter "invariant" object recognition? Journal of Neurophysiology. 102: 360-76. PMID 19439676 DOI: 10.1152/jn.90745.2008  1
2009 Zoccolan D, Oertelt N, DiCarlo JJ, Cox DD. A rodent model for the study of invariant visual object recognition. Proceedings of the National Academy of Sciences of the United States of America. 106: 8748-53. PMID 19429704 DOI: 10.1073/pnas.0811583106  1
2009 Pinto N, DiCarlo JJ, Cox DD. How far can you get with a modern face recognition test set using only simple features? 2009 Ieee Computer Society Conference On Computer Vision and Pattern Recognition Workshops, Cvpr Workshops 2009. 2591-2598. DOI: 10.1109/CVPRW.2009.5206605  1
2008 Cox DD, DiCarlo JJ. Does learned shape selectivity in inferior temporal cortex automatically generalize across retinal position? The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 28: 10045-55. PMID 18829962 DOI: 10.1523/JNEUROSCI.2142-08.2008  1
2008 Cox DD, Papanastassiou AM, Oreper D, Andken BB, Dicarlo JJ. High-resolution three-dimensional microelectrode brain mapping using stereo microfocal X-ray imaging. Journal of Neurophysiology. 100: 2966-76. PMID 18815345 DOI: 10.1152/jn.90672.2008  1
2008 Pinto N, Cox DD, DiCarlo JJ. Why is real-world visual object recognition hard? Plos Computational Biology. 4: e27. PMID 18225950 DOI: 10.1371/journal.pcbi.0040027  1
2007 Balas B, Cox D, Conwell E. The effect of real-world personal familiarity on the speed of face information processing Plos One. 2. PMID 18030351 DOI: 10.1371/journal.pone.0001223  1
2007 DiCarlo JJ, Cox DD. Untangling invariant object recognition. Trends in Cognitive Sciences. 11: 333-41. PMID 17631409 DOI: 10.1016/j.tics.2007.06.010  1
2005 Zoccolan D, Cox DD, DiCarlo JJ. Multiple object response normalization in monkey inferotemporal cortex. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 25: 8150-64. PMID 16148223 DOI: 10.1523/JNEUROSCI.2058-05.2005  1
2005 Cox DD, Meier P, Oertelt N, DiCarlo JJ. 'Breaking' position-invariant object recognition. Nature Neuroscience. 8: 1145-7. PMID 16116453 DOI: 10.1038/nn1519  1
2004 Cox D, Meyers E, Sinha P. Contextually evoked object-specific responses in human visual cortex. Science (New York, N.Y.). 304: 115-7. PMID 15001712 DOI: 10.1126/science.1093110  1
2003 Cox DD, Savoy RL. Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex. Neuroimage. 19: 261-70. PMID 12814577 DOI: 10.1016/S1053-8119(03)00049-1  1
2003 Meyers E, Cox DD, Sinha P. Neural responses to contextually defined faces Journal of Vision. 3: 101a. DOI: 10.1167/3.9.101  1
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