House Price Prediction using Satellite Imagery
Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:6EFHI7A5record.jsonopen to challenge →
classification
cs.LG
stat.ML
keywords
housemodelspricesatelliteaccuracyachieveangelesassessment
read the original abstract
In this paper we show how using satellite images can improve the accuracy of housing price estimation models. Using Los Angeles County's property assessment dataset, by transferring learning from an Inception-v3 model pretrained on ImageNet, we could achieve an improvement of ~10% in R-squared score compared to two baseline models that only use non-image features of the house.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.