What and where : a Bayesian inference theory of visual attention

What and where : a Bayesian inference theory of visual attention

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.

Bibliográfalaš dieđut
Váldodahkki:	Chikkerur, Sharat S
Eará dahkkit:	Tomaso Poggio.
Materiálatiipa:	Oahppočájánas
Giella:	eng
Almmustuhtton:	Massachusetts Institute of Technology 2011
Fáttát:	Electrical Engineering and Computer Science.
Liŋkkat:	http://hdl.handle.net/1721.1/62387

Geahča maid

What and Where: A Bayesian inference theory of visual attention
Dahkki: Chikkerur, Sharat, et al.
Almmustuhtton: (2011)

A Bayesian inference theory of attention: neuroscience and algorithms
Dahkki: Chikkerur, Sharat, et al.
Almmustuhtton: (2009)

Attention as a Bayesian inference process
Dahkki: Chikkerur, Sharat, et al.
Almmustuhtton: (2012)

An integrated model of visual attention using shape-based features
Dahkki: Poggio, Tomaso, et al.
Almmustuhtton: (2009)

Attentive processing improves object recognition
Dahkki: Chikkerur, Sharat, et al.
Almmustuhtton: (2009)

Bayesian inference algorithm on Raw
Dahkki: Luong, Alda
Almmustuhtton: (2006)

Bayesian population inference for effective connectivity
Dahkki: Cosman, Eric Richard, 1977-
Almmustuhtton: (2008)

A family of algorithms for approximate Bayesian inference
Dahkki: Minka, Thomas Peter
Almmustuhtton: (2014)

WHERE AND WHAT IN VISUAL-SEARCH
Dahkki: Atkinson, J, et al.
Almmustuhtton: (1989)

'Where' and 'what' in visual search.
Dahkki: Atkinson, J, et al.
Almmustuhtton: (1989)

Visualizing inference
Dahkki: Henke, Joseph D
Almmustuhtton: (2014)

Visual routines and attention
Dahkki: Rao, Satyajit, 1965-
Almmustuhtton: (2009)

Bayesian time series models and scalable inference
Dahkki: Johnson, Matthew James, Ph. D. Massachusetts Institute of Technology
Almmustuhtton: (2014)

Computing 'where' and 'what' in the visual system
Dahkki: Braddick, O
Almmustuhtton: (1993)

Approximations in the HMAX Model
Dahkki: Chikkerur, Sharat, et al.
Almmustuhtton: (2011)

Neural Bayesian goal inference for symbolic planning domains
Dahkki: Mann, Jordyn(Jordyn L.)
Almmustuhtton: (2021)

Scaling Bayesian inference : theoretical foundations and practical methods
Dahkki: Huggins, Jonathan H. (Jonathan Hunter)
Almmustuhtton: (2018)

Analysis of word-order universals using Bayesian phylogenetic inference
Dahkki: Ho, Pangus
Almmustuhtton: (2013)

Efficient IC statistical modeling and extraction using a Bayesian inference framework
Dahkki: Yu, Li, Ph. D. Massachusetts Institute of Technology
Almmustuhtton: (2015)

The role of fixation and visual attention in object recognition
Dahkki: Lakshmi Ratan, Aparna
Almmustuhtton: (2007)

Visual attention models for far-field scene analysis
Dahkki: Ižo, Tomáš, 1979-
Almmustuhtton: (2008)

Bio-inspired computation : where we stand and what’s next
Dahkki: Del Ser, Javier, et al.
Almmustuhtton: (2020)

Where are they looking?
Dahkki: Recasens, Adriá (Recasens Continente)
Almmustuhtton: (2016)

User adaptive Web morphing : an implementation of a Web-based Bayesian inference engine with Gittins' Index
Dahkki: Lee, Clarence, M. Eng. Massachusetts Institute of Technology
Almmustuhtton: (2009)

Visual area V5/MT remembers "what" but not "where".
Dahkki: Campana, G, et al.
Almmustuhtton: (2006)

Disentangling time constant and time dependent hidden state in time series with variational Bayesian inference
Dahkki: Grullon, Dylan Emanuel Centeno.
Almmustuhtton: (2020)

Bayesian inference for biological time series
Dahkki: Creswell, R
Almmustuhtton: (2023)

Towards practical theory : Bayesian optimization and optimal exploration
Dahkki: Kawaguchi, Kenji, Ph. D. Massachusetts Institute of Technology
Almmustuhtton: (2016)

Similarity-based virtual screening with a bayesian inference network
Dahkki: Abdo, Ammar, et al.
Almmustuhtton: (2008)

Graphical models and variational Bayesian inference for financial networks
Dahkki: Xin, Luyin
Almmustuhtton: (2019)

A study on dual topic models and bayesian topic model inference
Dahkki: Rugeles, Daniel
Almmustuhtton: (2020)

Demonstration of Bayesian inference and Bayesian experimental design in a model film/substrate inference problem
Dahkki: Aggarwal, Raghav
Almmustuhtton: (2016)

Watching where you look: modulation of visual processing of foveal stimuli by spatial attention.
Dahkki: Miniussi, C, et al.
Almmustuhtton: (2002)

Visual attention model analysis and benchmarking
Dahkki: Tan, Weisheng.
Almmustuhtton: (2011)

Visual attention modeling and its applications
Dahkki: Fang, Yuming
Almmustuhtton: (2013)

Finding visual attention regions in videos
Dahkki: Ang, Kenny Wen Bin
Almmustuhtton: (2010)

From what to where: neuropsychological evidence for implicit interactions between object- and space- based attention.
Dahkki: Humphreys, G, et al.
Almmustuhtton: (2003)

Visual attention: what inattention reveals about the brain
Dahkki: Husain, M
Almmustuhtton: (2019)

Attention for inference compilation
Dahkki: Harvey, W, et al.
Almmustuhtton: (2022)

A multiscale framework for Bayesian inference in elliptic problems
Dahkki: Parno, Matthew David
Almmustuhtton: (2011)