MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
Search 
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Search
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Search
JavaScript is disabled for your browser. Some features of this site may not work without it.

Search

Show Advanced FiltersHide Advanced Filters

Filters

Use filters to refine the search results.

Now showing items 11-20 of 115

  • Sort Options:
  • Relevance
  • Title Asc
  • Title Desc
  • Issue Date Asc
  • Issue Date Desc
  • Results Per Page:
  • 5
  • 10
  • 20
  • 40
  • 60
  • 80
  • 100
Thumbnail

Priors Stabilizers and Basis Functions: From Regularization to Radial, Tensor and Additive Splines 

Girosi, Federico; Jones, Michael; Poggio, Tomaso (1993-06-01)
We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this ...
Thumbnail

Direction Estimation of Pedestrian from Images 

Shimizu, Hiroaki; Poggio, Tomaso (2003-08-27)
The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots.We introduce an approach for estimating the walking direction of people ...
Thumbnail

Examining high level neural representations of cluttered scenes 

Meyers, Ethan; Embark, Hamdy; Freiwald, Winrich; Serre, Thomas; Kreiman, Gabriel; e.a. (2010-07-29)
Humans and other primates can rapidly categorize objects even when they are embedded in complex visual scenes (Thorpe et al., 1996; Fabre-Thorpe et al., 1998). Studies by Serre et al., 2007 have shown that the ability of ...
Thumbnail

Mathematics of the Neural Response 

Caponnetto, Andrea; Poggio, Tomaso; Bouvrie, Jake; Rosasco, Lorenzo; Smale, Steve (2008-11-26)
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 ...
Thumbnail

On a model of visual cortex: learning invariance and selectivity 

Caponnetto, Andrea; Poggio, Tomaso; Smale, Steve (2008-04-04)
In this paper we present a class of algorithms for similarity learning on spaces of images. The general framework that we introduce is motivated by some well-known hierarchical pre-processing architectures for object ...
Thumbnail

Learning and Invariance in a Family of Hierarchical Kernels 

Wibisono, Andre; Bouvrie, Jake; Rosasco, Lorenzo; Poggio, Tomaso (2010-07-30)
Understanding invariance and discrimination properties of hierarchical models is arguably the key to understanding how and why such models, of which the the mammalian visual system is one instance, can lead to good ...
Thumbnail

Neurons That Confuse Mirror-Symmetric Object Views 

Mutch, Jim; Leibo, Joel Z; Smale, Steve; Rosasco, Lorenzo; Poggio, Tomaso (2010-12-31)
Neurons in inferotemporal cortex that respond similarly to many pairs of mirror-symmetric images -- for example, 45 degree and -45 degree views of the same face -- have often been reported. The phenomenon seemed to be an ...
Thumbnail

Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures 

Rifkin, Ryan; Bouvrie, Jake; Schutte, Ken; Chikkerur, Sharat; Kouh, Minjoon; e.a. (2007-02-01)
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 ...
Thumbnail

A Trainable Object Detection System: Car Detection in Static Images 

Papageorgiou, Constantine P.; Poggio, Tomaso (1999-10-13)
This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a ...
Thumbnail

Model-Based Matching by Linear Combinations of Prototypes 

Jones, Michael J.; Poggio, Tomaso (1996-12-01)
We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call ...
  • 1
  • 2
  • 3
  • 4
  • 5
  • . . .
  • 12

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CommunityBy Issue DateAuthorsTitlesSubjects

My Account

Login

Discover

Author
Poggio, Tomaso (115)
Rosasco, Lorenzo (10)Girosi, Federico (9)Serre, Thomas (8)Mutch, Jim (7)Bouvrie, Jake (5)Chikkerur, Sharat (5)Hurlbert, Anya (5)Leibo, Joel Z (5)Yokono, Jerry Jun (5)... View MoreSubjectAI (25)object recognition (13)Artificial Intelligence (6)MIT (6)regularization (6)learning (5)classification (4)computer vision (4)local descriptor (4)inferior temporal cortex (3)... View MoreDate Issued2010 - 2013 (20)2000 - 2009 (36)1990 - 1999 (37)1980 - 1989 (22)Has File(s)Yes (115)

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Instagram YouTube

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.