Back to Results
First PageMeta Content
Inertia / Working memory / Ethology / Physics / Science / Cognitive science


Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model Edward Vul, Michael C. Frank, and Joshua B. Tenenbaum Department of Brain and Cognitive Sciences Ma
Add to Reading List

Document Date: 2010-10-21 13:51:24

Open Document

File Size: 641,97 KB

Share Result on Facebook

City

Cambridge / Newport / /

Company

Harvard University Press / Neural Information Processing Systems / /

Country

United States / /

/

Facility

Cognitive Sciences Massachusetts Institute of Technology Cambridge / /

IndustryTerm

visual search / information processing / classical tracking algorithm / analytical solutions / human online sentence processing / /

NaturalFeature

N(mt / /

Organization

Joshua B. Tenenbaum Department of Brain / Massachusetts Institute of Technology / EV / Institute of Technology Cambridge / Harvard University / George Alvarez Department of Psychology Harvard University Cambridge / National Science Foundation / /

Person

George Alvarez / Daphne Bavelier / Edward Vul / Michael C. Frank / Joshua B. Tenenbaum / /

/

Position

Fisher / and J. Enns / dynamic probabilistic model / /

ProgrammingLanguage

visual objects / A# / /

ProvinceOrState

Rhode Island / Massachusetts / /

Technology

classical tracking algorithm / /

SocialTag