A feedforward architecture accounts for rapid categorization Export

@article{serre.et.al.2007, abstract = {Primates are remarkably good at recognizing objects. The level of performance of their visual system and its robustness to image degradations still surpasses the best computer vision systems despite decades of engineering effort. In particular, the high accuracy of primates in ultra rapid object categorization and rapid serial visual presentation tasks is remarkable. Given the number of processing stages involved and typical neural latencies, such rapid visual processing is likely to be mostly feedforward. Here we show that a specific implementation of a class of feedforward theories of object recognition (that extend the Hubel and Wiesel simple-to-complex cell hierarchy and account for many anatomical and physiological constraints) can predict the level and the pattern of performance achieved by humans on a rapid masked animal vs. non-animal categorization task. 10.1073/pnas.0700622104}, author = {Serre, Thomas and Oliva, Aude and Poggio, Tomaso}, citeulike-article-id = {1270316}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0700622104}, citeulike-linkout-1 = {http://www.pnas.org/content/104/15/6424.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/104/15/6424.full.pdf}, citeulike-linkout-3 = {http://www.pnas.org/cgi/content/abstract/104/15/6424}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/17404214}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=17404214}, day = {10}, doi = {10.1073/pnas.0700622104}, journal = {PNAS}, keywords = {categorization, computational, hierarchical, learning, memory, model, neuroscience, object, unsupervised}, month = {April}, number = {15}, pages = {6424--6429}, posted-at = {2009-10-22 11:30:46}, priority = {0}, title = {A feedforward architecture accounts for rapid categorization}, url = {http://dx.doi.org/10.1073/pnas.0700622104}, volume = {104}, year = {2007} }

TY - JOUR ID - serre.et.al.2007 L3 - citeulike-article-id:1270316 N2 - Primates are remarkably good at recognizing objects. The level of performance of their visual system and its robustness to image degradations still surpasses the best computer vision systems despite decades of engineering effort. In particular, the high accuracy of primates in ultra rapid object categorization and rapid serial visual presentation tasks is remarkable. Given the number of processing stages involved and typical neural latencies, such rapid visual processing is likely to be mostly feedforward. Here we show that a specific implementation of a class of feedforward theories of object recognition (that extend the Hubel and Wiesel simple-to-complex cell hierarchy and account for many anatomical and physiological constraints) can predict the level and the pattern of performance achieved by humans on a rapid masked animal vs. non-animal categorization task. 10.1073/pnas.0700622104 IS - 15 JF - PNAS EP - 6429 TI - A feedforward architecture accounts for rapid categorization VL - 104 SP - 6424 KW - categorization KW - computational KW - hierarchical KW - learning KW - memory KW - model KW - neuroscience KW - object KW - unsupervised AU - Serre, Thomas AU - Oliva, Aude AU - Poggio, Tomaso PY - 2007/04/10/ UR - http://dx.doi.org/10.1073/pnas.0700622104 ER -