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25 years of CNNs: Can we compare to human abstraction capabilities?
July 28, 2016 Β· Declared Dead Β· π International Conference on Artificial Neural Networks
"No code URL or promise found in abstract"
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Authors
Sebastian Stabinger, Antonio RodrΓguez-SΓ‘nchez, Justus Piater
arXiv ID
1607.08366
Category
cs.CV: Computer Vision
Citations
57
Venue
International Conference on Artificial Neural Networks
Last Checked
5 months ago
Abstract
We try to determine the progress made by convolutional neural networks over the past 25 years in classifying images into abstractc lasses. For this purpose we compare the performance of LeNet to that of GoogLeNet at classifying randomly generated images which are differentiated by an abstract property (e.g., one class contains two objects of the same size, the other class two objects of different sizes). Our results show that there is still work to do in order to solve vision problems humans are able to solve without much difficulty.
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