Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/106962
Author(s): Rui Pedro da Silva Rodrigues Machado
Title: Image visual similarity with deep learning: application to a fashion ecommerce company
Issue Date: 2017-07-25
Abstract: Deep learning is a very trendy topic now, showing high accuracy in image based systems that can go from image segmentation to object detection and image retrieval. Because of this, multiple researchers and companies have been building and sharing work in the community, including pre-trained convolutional neural networks, available for public use. This work follows the trend and delivers an experimental study using deep learning for building a visually similar image retrieval application, comparing three different convolutional neural architectures for feature extraction and six distance indexes for similarity calculation in a real-world image retrieval problem, using real data from a fashion e-commerce platform from Morocco. After testing all the different combinations, we can conclude that for this dataset, Vgg19 combined with a correlation coefficient for similarity calculation is the tuple that best maximizes the similarity between a search image and its retrieved neighbors.
Subject: Economia e gestão
Call Number: 209524
URI: http://hdl.handle.net/10216/106962
Document Type: Relatório de Projeto
Rights: openAccess
License: https://creativecommons.org/licenses/by/4.0/
Appears in Collections:FEP - Relatório de Projeto

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