# House Price Prediction using Satellite Imagery

Source: [House Price Prediction using Satellite Imagery](<https://www.sota2.com/research/paper/68fa69f11e209131cea25225>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:47.876Z

Authors: Sina Jandaghi Semnani, Hoormazd Rezaei

Published: 2021-05-13T03:25:32.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2105.06060>)

[PDF](<https://arxiv.org/pdf/2105.06060.pdf>)