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		<isbn>978-85-7669-273-7</isbn>
		<citationkey>TakahashiKaneYama:1995:InAt3D</citationkey>
		<title>Radiosity and Hopfield neural networks applied to inverse lighting design: initial attempts in 3D</title>
		<format>Impresso, On-line.</format>
		<year>1995</year>
		<numberoffiles>1</numberoffiles>
		<size>1511 KiB</size>
		<author>Takahashi, Kentaro,</author>
		<author>Kaneda, Kazufumi,</author>
		<author>Yamashita, Hideo,</author>
		<affiliation>Faculty of Engineering of Hiroshima University</affiliation>
		<affiliation>Faculty of Engineering of Hiroshima University</affiliation>
		<affiliation>Faculty of Engineering of Hiroshima University</affiliation>
		<editor>Lotufo, Roberto de Alencar,</editor>
		<editor>Mascarenhas, Nelson Delfino d'Ávila,</editor>
		<e-mailaddress>cintiagraziele.silva@gmail.com</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 8 (SIBGRAPI)</conferencename>
		<conferencelocation>São Carlos, SP, Brazil</conferencelocation>
		<date>25-27 Oct. 1995</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<pages>323-324</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Comunicação Técnica</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>radiosity, Hopfield neural networks, Reverse lighting design, lighting 3D environments.</keywords>
		<abstract>This technical communication describes the employment of a new method that gathers radiosity and the Hopfield Neural Network applied to the task of designing the lighting of a closed space and considering interreflection of light. The proposed method finds the best luminous intensity, according to a showcase of realizable luminous intensities that are passive of being produced by the industry or be available in the market. Partial results of the algorithms applied to the lighting of 3D environments are presented.</abstract>
		<type>Geral (Comunicações)</type>
		<language>en</language>
		<targetfile>54 Radiosity and hopfield neural.pdf</targetfile>
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