Undergraduate thesis presented at the University of São Paulo. Abstract: Using street images extracted from Google Street View and demographic data from the 2010 IBGE Census, this study proposes a predictive model based on deep learning to be used as an estimator of socioeconomic indicators. In addition, it presents the intermediate experiments and the adjustments that were made to the methodology of the final experiment. via: pcs.usp.brAcknowledgments: The PARSEC project is funded by the Belmont Forum, Collaborative Research Action on Science-Driven e-Infrastructures Innovation
In many cities of the Global South, informal and deprived neighborhoods, also commonly called slums,...
Targeted socio-economic policies require an accurate understanding of a country’s demographic makeup...
This hands on session aims to exemplify a Deep learning workflow for socioeconomic estimation using ...
International audienceSocioeconomic indicators are essential to help design and monitor the impact o...
Abstract: Key measures of socioeconomic indicators are essential for making informed policy decisio...
(1) Background: Evidence-based policymaking requires data about the local population’s socioec...
Abstract Due to low awareness and low investment in data collection and processing in developing co...
First release of the repository PARSECworld/streetsValeRibeira This code was used to generate resul...
Undegraduate thesis presented at the University of São Paulo. Abstract This work has the objective...
Data on key measures of socioeconomic development can be a powerful tool to assist government polici...
Undergraduate monograph Abstract: Parsec project aims to apply Data Science and Machine Learning t...
In this slides we share an ongoing work presented at AGU Fall Meeting 2020. We present an approach a...
Data collected at large scale and low cost (e.g. satellite and street level imagery) have the potent...
High-resolution daytime satellite imagery has become a promising source to study economic activities...
Machine learning methods have achieved human-level accuracies in many computer vision and natural la...
In many cities of the Global South, informal and deprived neighborhoods, also commonly called slums,...
Targeted socio-economic policies require an accurate understanding of a country’s demographic makeup...
This hands on session aims to exemplify a Deep learning workflow for socioeconomic estimation using ...
International audienceSocioeconomic indicators are essential to help design and monitor the impact o...
Abstract: Key measures of socioeconomic indicators are essential for making informed policy decisio...
(1) Background: Evidence-based policymaking requires data about the local population’s socioec...
Abstract Due to low awareness and low investment in data collection and processing in developing co...
First release of the repository PARSECworld/streetsValeRibeira This code was used to generate resul...
Undegraduate thesis presented at the University of São Paulo. Abstract This work has the objective...
Data on key measures of socioeconomic development can be a powerful tool to assist government polici...
Undergraduate monograph Abstract: Parsec project aims to apply Data Science and Machine Learning t...
In this slides we share an ongoing work presented at AGU Fall Meeting 2020. We present an approach a...
Data collected at large scale and low cost (e.g. satellite and street level imagery) have the potent...
High-resolution daytime satellite imagery has become a promising source to study economic activities...
Machine learning methods have achieved human-level accuracies in many computer vision and natural la...
In many cities of the Global South, informal and deprived neighborhoods, also commonly called slums,...
Targeted socio-economic policies require an accurate understanding of a country’s demographic makeup...
This hands on session aims to exemplify a Deep learning workflow for socioeconomic estimation using ...