Blog

Learn About Our Meetup

5000+ Members

MEETUPS

LEARN, CONNECT, SHARE

Join our meetup, learn, connect, share, and get to know your Toronto AI community. 

JOB POSTINGS

INDEED POSTINGS

Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.

CONTACT

CONNECT WITH US

Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.

[R] Applying Machine Learning and Discrete Choice Modeling to understand the quality of urban landscape

[R] Applying Machine Learning and Discrete Choice Modeling to understand the quality of urban landscape

Wekun (wekun.ing.puc.cl) is a game that seeks to understand how people perceive public space and, thus, understand what determines the quality of these spaces.

We ask people to chose between images to measure their preferences. Then, the information collected is processed with Machine Learning algorithms and discrete choice models, in order to understand the role played by different elements of the built environment and nature in the preferences of people. The methodology is not new (links below), but we have incorporated a section to register sociodemographic information aiming to find heterogeneity among observers. We use Discrete Choice Modelling as a benchmark to Machine Learning Algorithms, typically referred to as black boxes, to overcome the explainability problems involved with them.

https://i.redd.it/xamzwiv0a9231.jpg

Please comment on the following subjects to help us!

  1. Any recommendation of semantic segmentation algorithms? or Object detection?
  2. For the success of this research, we need your help evaluating photos of public spaces and sharing this message to have the opinion of more people!

Some references:

Rossetti, T., Lobel, H., Rocco, V., & Hurtubia, R. (2019). Explaining subjective perceptions of public spaces as a function of the built environment: A massive data approach. Landscape and urban planning, 181, 169-178. (link)

Salesses, P., Schechtner, K., & Hidalgo, C. A. (2013). The collaborative image of the city: mapping the inequality of urban perception. PloS one, 8(7), e68400. (link)

Dubey, A., Naik, N., Parikh, D., Raskar, R., & Hidalgo, C. A. (2016, October). Deep learning the city: Quantifying urban perception at a global scale. In European conference on computer vision (pp. 196-212). Springer, Cham. (link)

submitted by /u/tiramirez
[link] [comments]

Next Meetup

 

Days
:
Hours
:
Minutes
:
Seconds

 

Plug yourself into AI and don't miss a beat

 


Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.