The Observatory of Public Spending (or ODP, in Portuguese) is a special unit of Brazil's Ministry of Transparency, Monitoring and Office of the Comptroller-General (or CGU, in Portuguese) responsible for monitoring public spending and gathering managerial and audit information to support the work of CGU internal auditors. One of the most important themes monitored by this unit is Public Procurements and Government Suppliers which have won these procurement processes. Image analysis of many of these suppliers headquarters revealed suspicious landscapes, such as rural areas, isolated places or slums. These landscapes could be an indication of fake suppliers with poor capacity of delivering public goods and services. However, checking thousands of landscapes in order to find these fake suppliers would be a very expensive task. Our objective then is to discover what are the possible groups of scenes involving government suppliers, given that these images were not previously labeled, as automatically as possible. For that reason, we used Places CNN, a pretrained convolutional neural network for scene recognition presented by Zhou et al., which was trained on 205 scene categories with 2.5 million images, for scene recognition on Brazilian Government Suppliers.
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