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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 17 of 17 1 Spatial IQ Test for AI Hilton, Erwin; Liao, Qianli; Poggio, Tomaso. - 2017 BASE Show details 2 Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing Tan, Cheston; Poggio, Tomaso. - : Public Library of Science, 2016 BASE Show details 3 Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing Tan, Cheston; Poggio, Tomaso A In: Public Library of Science (2016) BASE Show details 4 Neural tuning size is a key factor underlying holistic face processing Tan, Cheston; Poggio, Tomaso. - : Center for Brains, Minds and Machines (CBMM), arXiv, 2014 BASE Show details 5 Faces as a "Model Category" for Visual Object Recognition Tan, Cheston; Poggio, Tomaso. - 2013 Abstract: Visual recognition is an important ability that is central to many everyday tasks such as reading, navigation and social interaction, and is therefore actively studied in neuroscience, cognitive psychology and artificial intelligence. There exist thousands of object categories, all of which pose similar challenges to biological and artificial visual systems: accurate recognition under varying location, scale, view angle, illumination and clutter. In many areas of science, important discoveries have been made using "model organisms" such as fruit flies, mice and macaques. For the thousands of object categories, the important and well-studied category of faces could potentially serve as a "model category" upon which efforts are focused, and from which fundamental insights are drawn. However, it has been hotly debated whether faces are processed by the brain in a manner fundamentally different from other categories. Here we show that "neural tuning size" -- a single parameter in a computational model of object processing -- is able to account for important face-specific phenomena. Thus, surprisingly, "face-like" processing is explainable by physiological mechanisms that differ only quantitatively from "object-like" processing. Our computational proof-of-principle provides specific neural tuning properties that correspond to the so-far qualitative and controversial notion of "holistic" face processing. Overall, faces may be a viable model category. Since faces are highly amenable to complementary experimental techniques like functional MRI, electrophysiology, electroencephalography and transcranial magnetic stimulation, this further raises the odds that the algorithms and neural circuits underlying visual recognition may first be solved for faces. With faces serving as a model category, the great scientific challenge of understanding and reverse-engineering general visual recognition can be greatly accelerated. Keyword: composite effect; face recognition; holistic processing; inversion effect; object recognition URL: http://hdl.handle.net/1721.1/77936 BASE Hide details 6 Learning On-Line from a Few Examples Poggio, Tomaso In: DTIC (2009) BASE Show details 7 Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures Rifkin, Ryan; Bouvrie, Jake; Schutte, Ken. - 2007 BASE Show details 8 Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures Rifkin, Ryan; Bouvrie, Jake; Schutte, Ken. - 2007 BASE Show details 9 Trainable Videorealistic Speech Animation Ezzat, Tony; Geiger, Gadi; Poggio, Tomaso In: DTIC (2006) BASE Show details 10 General conditions for predictivity in learning theory Poggio, Tomaso; Rifkin, Ryan; Mukherjee, Sayan... In: Nature. - London : Macmillan Publishers Limited, part of Springer Nature 428 (2004) 6981, 419-422 BLLDB Show details 11 High-level learning of early visual tasks Sinha, Pawan; Poggio, Tomaso In: Perceptual learning (Cambridge, Mass, 2002), p. 273-298 MPI für Psycholinguistik Show details 12 Sparse correlation kernel reconstruction and superresolution Papageorgiou, Constantine P.; Girosi, F.; Poggio, Tomaso In: Probabilistic models of the brain (Cambridge, 2002), p. 155-180 MPI für Psycholinguistik Show details 13 Perceptual learning Fahle, Manfred; Poggio, Tomaso. - Cambridge, Mass : MIT Press, 2002 MPI für Psycholinguistik Show details 14 Categorical representation of visual stimuli in the primate prefrontal cortex Freedman, David J.; Riesenhuber, Maximilian; Poggio, Tomaso... In: Science. - Washington, DC : AAAS, American Assoc. for the Advancement of Science 291 (2001) 5502, 312-316 BLLDB Show details 15 Observations on cortical mechanisms for object recognition and learning Poggio, Tomaso A.; Hurlbert, Anya In: Large-scale neuronal theories of the brain (Cambridge, Mass, 1994), p. 153-182 MPI für Psycholinguistik Show details 16 Computation of motion by real neurons Grzywacz, Norberto M.; Poggio, Tomaso In: An introduction to neural and electronic networks (San Diego, 1990), p. 379-407 MPI für Psycholinguistik Show details 17 Making machines (and artificial intelligence) see Hurlbert, Anya; Poggio, Tomaso In: The artificial intelligence debate (Cambridge, Mass., 1988), P. 213-240 MPI für Psycholinguistik Show details

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