[Theory] REMINDER: 4/15 Distinguished Lecture Series: Pietro Perona, California Institute of Technology

[Mary Marre]

*TTIC Distinguished Lecture Series:  *
Pietro Perona <https://eas.caltech.edu/people/perona>*, California
Institute of Technology*

 [image: image.png]
Thursday, April 15, 2021 at 11:10 am CT
*Lecture will be held virtually:  *

*Register in advance here*
<https://uchicagogroup.zoom.us/webinar/register/WN_gJNlLLSESy2r8-oSzgKC-g>

*Pietro Perona*

*Allen E. Puckett Professor of Electrical Engineering and Computation and
Neural Systems*

*Director of the National Science Foundation Engineering Research Center
in *

*Neuromorphic Systems Engineering*


------------------------------


*Title:* A Sense for Number and Quantity as an Emergent Property of a
Manipulating Agent


*Abstract: *The ability to understand and manipulate numbers and quantities
emerges during childhood, but the mechanism through which this ability is
developed is still poorly understood. In particular, it is not known
whether acquiring such a `number sense' is possible without supervision
from a teacher.

To explore this question, we propose a model in which spontaneous and
undirected manipulation of small objects trains perception to predict the
resulting scene changes. We find that, from this task, a representation
emerges that supports understanding numbers and quantity. Emergent
properties include distinct categories for zero and the first few natural
numbers, a notion of order, and a signal that correlates with numerical
quantity. As a result, our model acquires the ability to estimate the
number of objects in the scene, as well as `subitization', i.e. the ability
to recognize at a glance the exact number of objects in small scenes. We
conclude that important aspects of a facility with numbers and quantities
may be learned without explicit teacher supervision.

Joint work with Neehar Kondapaneni

 *Bio: *Pietro Perona received a Ph.D. in electrical engineering and
computer science from the University of California, Berkeley, in 1990. In
1990, he was postdoctoral fellow at the International Computer Science
Institute at Berkeley. From 1990 to 1991, he was a postdoctoral fellow at
the Massachusetts Institute of Technology in the Laboratory for Information
and Decision Systems. In the fall of 1991, Perona joined the California
Institute of Technology as assistant professor. He became full professor in
1996 and the Allen E. Puckett Professor of Electrical Engineering and
Computation and Neural Systems in 2006. From 1999 to 2005, Perona was the
director of the National Science Foundation Center for Neuromorphic Systems
Engineering. Since 2005, he has led the Computation and Neural Systems
program at the California Institute of Technology.

Perona’s research focuses on the computational aspects of vision and
learning. He is known for the anisotropic diffusion equation, a partial
differential equation that filters image noise while enhancing region
boundaries. He is currently interested in visual recognition and in visual
analysis of behavior. In the early 2000s, Perona pioneered the study of
visual categorization. Currently, in collaboration with colleagues Michael
Dickinson and David Anderson, he applies machine vision to measuring and
analyzing the behavior of laboratory animals.

Perona is the recipient of the 2013 Longuet-Higgins Prize and of the 2010
Koenderink Prize for fundamental contributions in computer vision. He is
the recipient of the 2003 Institute of Electrical and Electronics
Engineers–Conference on Computer Vision and Pattern Recognition best paper
award. He is also the recipient of a 1996 NSF Presidential Young
Investigator Award.

Current Project: Outer Brain and Inner Brain: Computational Principles and
Interactions
Past Project: Neural computation of innate defensive behavioral decisions

*Host*: *Matthew Turk* <mturk at ttic.edu>




*Distinguished Lecture Series:* for questions and comments contact *Jinbo
Xu <j3xu at ttic.edu>**.*


[image: image.png]



*(Updated DLS poster attached)*


Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 517*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Tue, Apr 6, 2021 at 10:45 AM Mary Marre <mmarre at ttic.edu> wrote:

> *TTIC Distinguished Lecture Series:  *
> Pietro Perona <https://eas.caltech.edu/people/perona>*, California
> Institute of Technology*
>
>  [image: image.png]
> Thursday, April 15, 2021 at 11:10 am CT
> *Lecture will be held virtually:  *
>
> *Register in advance here*
> <https://uchicagogroup.zoom.us/webinar/register/WN_gJNlLLSESy2r8-oSzgKC-g>
>
> *Pietro Perona*
>
> *Allen E. Puckett Professor of Electrical Engineering and Computation and
> Neural Systems*
>
> *Director of the National Science Foundation Engineering Research Center
> in *
>
> *Neuromorphic Systems Engineering*
>
>
> ------------------------------
>
>
> *Title:* A Sense for Number and Quantity as an Emergent Property of a
> Manipulating Agent
>
>
> *Abstract: *The ability to understand and manipulate numbers and
> quantities emerges during childhood, but the mechanism through which this
> ability is developed is still poorly understood. In particular, it is not
> known whether acquiring such a `number sense' is possible without
> supervision from a teacher.
>
> To explore this question, we propose a model in which spontaneous and
> undirected manipulation of small objects trains perception to predict the
> resulting scene changes. We find that, from this task, a representation
> emerges that supports understanding numbers and quantity. Emergent
> properties include distinct categories for zero and the first few natural
> numbers, a notion of order, and a signal that correlates with numerical
> quantity. As a result, our model acquires the ability to estimate the
> number of objects in the scene, as well as `subitization', i.e. the ability
> to recognize at a glance the exact number of objects in small scenes. We
> conclude that important aspects of a facility with numbers and quantities
> may be learned without explicit teacher supervision.
>
> Joint work with Neehar Kondapaneni
>
>  *Bio: *Pietro Perona received a Ph.D. in electrical engineering and
> computer science from the University of California, Berkeley, in 1990. In
> 1990, he was postdoctoral fellow at the International Computer Science
> Institute at Berkeley. From 1990 to 1991, he was a postdoctoral fellow at
> the Massachusetts Institute of Technology in the Laboratory for Information
> and Decision Systems. In the fall of 1991, Perona joined the California
> Institute of Technology as assistant professor. He became full professor in
> 1996 and the Allen E. Puckett Professor of Electrical Engineering and
> Computation and Neural Systems in 2006. From 1999 to 2005, Perona was the
> director of the National Science Foundation Center for Neuromorphic Systems
> Engineering. Since 2005, he has led the Computation and Neural Systems
> program at the California Institute of Technology.
>
> Perona’s research focuses on the computational aspects of vision and
> learning. He is known for the anisotropic diffusion equation, a partial
> differential equation that filters image noise while enhancing region
> boundaries. He is currently interested in visual recognition and in visual
> analysis of behavior. In the early 2000s, Perona pioneered the study of
> visual categorization. Currently, in collaboration with colleagues Michael
> Dickinson and David Anderson, he applies machine vision to measuring and
> analyzing the behavior of laboratory animals.
>
> Perona is the recipient of the 2013 Longuet-Higgins Prize and of the 2010
> Koenderink Prize for fundamental contributions in computer vision. He is
> the recipient of the 2003 Institute of Electrical and Electronics
> Engineers–Conference on Computer Vision and Pattern Recognition best paper
> award. He is also the recipient of a 1996 NSF Presidential Young
> Investigator Award.
>
> Current Project: Outer Brain and Inner Brain: Computational Principles and
> Interactions
> Past Project: Neural computation of innate defensive behavioral decisions
>
> *Host*: *Matthew Turk* <mturk at ttic.edu>
>
>
>
>
> *Distinguished Lecture Series:* for questions and comments contact *Jinbo
> Xu <j3xu at ttic.edu>**.*
>
>
> [image: image.png]
>
>
>
> Mary C. Marre
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Chicago, IL  60637*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
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