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

This guide is for authors who are preparing papers for the Taylor & Francis journal International Journal of Geographical Information Science (tGIS ) using the LATEX 2ε document preparation system and the Class file tGIS2e.cls, which is available via the journal homepage on the Taylor & Francis website. Authors planning to submit their papers in LATEX2ε are advised to use tGIS2e.cls as early as possible in the creation of their files.

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.

A simple Tribhuvan University, Institute of Engineering, Masters Thesis proposal template 2017-12-14 v. 1.0.0 Copyright 2010-2017 by Shyam Krishna Khadka This template is inspired from Jesper Kjær Nielsen (jkn@es.aau.dk) AAU template which can be seen in some of the files.

Un modèle de présentation sur le thème graphique de l'Université de Lorraine; à adapter selon les besoins.

This document and its LaTeX source are meant as a guide to the Notre Dame Journal of Formal Logic’s (NDJFL) style and the style files ndjflart and jflnat.bst.

Modelo de Trabalho Acadêmico da FEA-RP em conformidade com a ABNT NBR 14724:2011 e Diretrizes para Confecção de Teses e Dissertações da USP

AME Fall '17 Senior Design