Gallery — Project / Lab Report

Adiabatic Flame Temperature

Criado a partir da classe abntex2, desenvolvida pelo Centro de Pesquisa em Arquitetura da Informação (CPAI)

PLANO DE PESQUISA INDIVIDUAL Criado a partir da classe abntex2, desenvolvida pelo Centro de Pesquisa em Arquitetura da Informação (CPAI)

Sencilla plantilla (no oficial) para informes o trabajos universitarios a una sola columna. Contiene paquetes para la inserción de gráficos e imágenes, así como de código informático (especialmente pensado para Octave y Matlab). Se incluyen diversos paquetes para la inserción de símbolos matemáticos y teoremas. Está totalmente habilitada para la escritura en español. La portada muestra el escudo de la Universidad de Oviedo.

This is a template for the report of Final Year Project (FYP) for the courses offered at the Universiti Teknology MARA (UiTM) Kelantan and also might be useful for other universities. This template was modified from the MMU Thesis template by LianTze Lim.

In most corruption scandals, the use of front companies for money laundering is almost ubiquitous. This work proposes to apply image classification to detect such organizations, through the use of Convolutional Neural Networks (CNN), namely the AlexNet architecture. The images are obtained by address search in Google Street View API, and the resulting classification will be further used along with other features to detect front com- panies in order to help the auditors from the Ministry of Transparency and Office of the Comptroller General (CGU, in Portuguese). To this moment, we applied classification to almost 15 thousand suppliers scenes with active contracts with the Brazilian Government until September 2016, obtained through data matching between the Government Purchases database and the Brazilian Federal Revenue Office database (more recent scenes should be added as this work progresses). Preliminary results with a pre-trained AlexNet CNN show the need for developing new scene classes more suited to the Brazilian context. In order to do this, we propose to apply clustering algorithms in features extracted from the last fully-connected layer of this net. The classes obtained will be used to fine-tune the AlexNet CNN for future classification, through the use of training from scratch or fine tuning techniques.

Modelo LaTex para preparação do documento final de Monografia TCC O modelo está em conformidade com ABNT NBR Faculdade do Piaui --------------------------------------------------------------------------- ---------------------------------------------------------------------------

Modelo LaTex para preparação do documento final de Monografia TCC O modelo está em conformidade com ABNT NBR Faculdade do Piaui

Modelo LaTex para preparação do documento final de TCC O modelo está em conformidade com ABNT NBR Faculdade do Piaui - FAPI