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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 BASE Show 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; Chikkerur, Sharat; Kouh, Minjoon; Ezzat, Tony; Poggio, Tomaso. - 2007 Abstract: A preliminary set of experiments are described in which a biologically-inspired computer vision system (Serre, Wolf et al. 2005; Serre 2006; Serre, Oliva et al. 2006; Serre, Wolf et al. 2006) designed for visual object recognition was applied to the task of phonetic classification. During learning, the systemprocessed 2-D wideband magnitude spectrograms directly as images, producing a set of 2-D spectrotemporal patch dictionaries at different spectro-temporal positions, orientations, scales, and of varying complexity. During testing, features were computed by comparing the stored patches with patches fromnovel spectrograms. Classification was performed using a regularized least squares classifier (Rifkin, Yeo et al. 2003; Rifkin, Schutte et al. 2007) trained on the features computed by the system. On a 20-class TIMIT vowel classification task, the model features achieved a best result of 58.74% error, compared to 48.57% error using state-of-the-art MFCC-based features trained using the same classifier. This suggests that hierarchical, feed-forward, spectro-temporal patch-based architectures may be useful for phoneticanalysis. Keyword: hierarchical models; phonetic classification; regularized least-squares; spectrotemporal patches URL: http://hdl.handle.net/1721.1/35835 BASE Hide 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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