TY - JOUR
T1 - Mathematics of the neural response
AU - Smale, S.
AU - Rosasco, L.
AU - Bouvrie, J.
AU - Caponnetto, A.
AU - Poggio, T.
PY - 2010/1
Y1 - 2010/1
N2 - We propose a natural image representation, the neural response, motivated by the neuroscience of the visual cortex. The inner product defined by the neural response leads to a similarity measure between functions which we call the derived kernel. Based on a hierarchical architecture, we give a recursive definition of the neural response and associated derived kernel. The derived kernel can be used in a variety of application domains such as classification of images, strings of text and genomics data. © SFoCM 2009.
AB - We propose a natural image representation, the neural response, motivated by the neuroscience of the visual cortex. The inner product defined by the neural response leads to a similarity measure between functions which we call the derived kernel. Based on a hierarchical architecture, we give a recursive definition of the neural response and associated derived kernel. The derived kernel can be used in a variety of application domains such as classification of images, strings of text and genomics data. © SFoCM 2009.
KW - Computer vision
KW - Kernels
KW - Unsupervised learning
UR - http://www.scopus.com/inward/record.url?scp=75849157565&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-75849157565&origin=recordpage
U2 - 10.1007/s10208-009-9049-1
DO - 10.1007/s10208-009-9049-1
M3 - RGC 21 - Publication in refereed journal
SN - 1615-3375
VL - 10
SP - 67
EP - 91
JO - Foundations of Computational Mathematics
JF - Foundations of Computational Mathematics
IS - 1
ER -