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		<citationkey>NogueiraVeloSant:2016:StDeLe</citationkey>
		<title>Statistical and Deep Learning Algorithms for Annotating and Parsing Clothing Items in Fashion Photographs</title>
		<format>On-line</format>
		<year>2016</year>
		<numberoffiles>1</numberoffiles>
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		<author>Nogueira, Keiller,</author>
		<author>Veloso, Adriano Alonso,</author>
		<author>Santos, Jefersson Alex dos,</author>
		<affiliation>Universidade Federal de Minas Gerais (UFMG)</affiliation>
		<affiliation>Universidade Federal de Minas Gerais (UFMG)</affiliation>
		<affiliation>Universidade Federal de Minas Gerais (UFMG)</affiliation>
		<editor>Aliaga, Daniel G.,</editor>
		<editor>Davis, Larry S.,</editor>
		<editor>Farias, Ricardo C.,</editor>
		<editor>Fernandes, Leandro A. F.,</editor>
		<editor>Gibson, Stuart J.,</editor>
		<editor>Giraldi, Gilson A.,</editor>
		<editor>Gois, João Paulo,</editor>
		<editor>Maciel, Anderson,</editor>
		<editor>Menotti, David,</editor>
		<editor>Miranda, Paulo A. V.,</editor>
		<editor>Musse, Soraia,</editor>
		<editor>Namikawa, Laercio,</editor>
		<editor>Pamplona, Mauricio,</editor>
		<editor>Papa, João Paulo,</editor>
		<editor>Santos, Jefersson dos,</editor>
		<editor>Schwartz, William Robson,</editor>
		<editor>Thomaz, Carlos E.,</editor>
		<e-mailaddress>keillernogueira@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)</conferencename>
		<conferencelocation>São José dos Campos, SP, Brazil</conferencelocation>
		<date>4-7 Oct. 2016</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Master's or Doctoral Work</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>Machine Learning, Image Annotation, Image Parsing, Descriptor, Visual Dictionary, Neural Networks, Deep Learning.</keywords>
		<abstract>Clothing identification has important roles in several areas. In this work, we present effective algorithms to automatically annotate and parse clothes from social media data. Clothing annotation tries to recognize each garment item that appears in a photo. Clothing parsing, in turn, locates and annotates each garment item in a photo. Both task pose interesting challenges for existing vision and recognition algorithms, such as distinguishing similar clothes or creating a pattern of a specific item. For the first task, two approaches, based on traditional algorithms, were proposed: (i) the pointwise one, and (ii) a multi-instance or pairwise approach. An evaluation show improvements of the proposed methods when compared to popular first choice algorithms that range from 20% to 30%. For the second task, a multi-scale convolutional network was proposed. At the end, a class is associated with each patch of the image. Experiments shows that the proposed method achieves promising results.</abstract>
		<language>en</language>
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		<usergroup>keillernogueira@gmail.com</usergroup>
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