Machine learning evolving computer vision: Estimating socioeconomic levels using satellite imagery

Kantar Mexico, a market researcher, explains how, by using widely available datasets, a state-of-the-art neural model and business knowledge, high value can be extracted at low cost from visual data.

Preface

How to extract great insights from satellite imagery? The last few years have seen enormous growth on Al-based data-enrichment techniques. Automatic sentiment and topic identification in text documents have become ubiquitous. Image classification, tagging, and brand-detection are now mainstream. Taking advantage of these techniques, we trained a model capable of identifying the Socioeconomic Group (SEG) of a delimited region relying solely on satellite imagery. The model, when joined with other geographical features, can be used to create rich attractiveness models, sampling frameworks and more.

Introduction

Artificial intelligence (Al) has become a buzzword. All Forbes 500 companies are now obliged...

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