Forest species recognition using deep convolutional neural networks

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2014, Pages 1103-1107

  Hafemann, Luiz G ^a   Oliveira, Luiz S ^a   Cavalin, Paulo ^b  

^a FEDERAL UNIVERSITY OF PARANÁ   (Brazil)

^b IBM RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONVOLUTION; DEEP LEARNING; DEEP NEURAL NETWORKS; FORESTRY; GABOR FILTERS; IMAGE TEXTURE; LEARNING SYSTEMS; OBJECT RECOGNITION; TEXTURES;

FOCUS OF RESEARCHES; HIGH-RESOLUTION TEXTURES; HIGHER RESOLUTION IMAGES; LEARNING TECHNIQUES; LOCAL BINARY PATTERNS; LOCAL PHASE QUANTIZATIONS; MICROSCOPIC IMAGE; TEXTURE CLASSIFICATION;

CONVOLUTIONAL NEURAL NETWORKS;

CLASSIFICATION; NEURAL NETWORKS; PATTERN RECOGNITION; PROBLEM SOLVING;

EID: 84919907124     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2014.199     Document Type: Conference Paper

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