articleJun 1, 2014GREEN OA

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

KTH Royal Institute of Technology

Indexed incrossref

Abstract

Recent results indicate that the generic descriptors extracted from the convolutional neural networks are very powerful. This paper adds to the mounting evidence that this is indeed the case. We report on a series of experiments conducted for different recognition tasks using the publicly available code and model of the OverFeat network which was trained to perform object classification on ILSVRC13. We use features extracted from the OverFeat network as a generic image representation to tackle the diverse range of recognition tasks of object image classification, scene recognition, fine grained recognition, attribute detection and image retrieval applied to a diverse set of datasets. We selected these tasks…

Citation impact

4,331
total citations
FWCI
312.87
Percentile
100%
References
70
Citations per year

Authors

4

Topics & keywords

Keywords
  • Computer science
  • Artificial intelligence
  • Convolutional neural network
  • Pattern recognition (psychology)
  • Classifier (UML)
  • Feature extraction
  • Contextual image classification
  • Support vector machine
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