Abstract
In this chapter, we investigate the possibility of reconstructing images from reduced dimensions and using narrow artificial intelligence frameworks. This is aimed at addressing the high execution time drawback witnessed when deep neural network frameworks are used. The lower dimensional data is obtained from the bottleneck layer of the deep autoencoder network; in this case, the number of reduced features is 30. The aim is to observe whether this approach preserves accuracy while minimizing execution time.
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Leke, C.A., Marwala, T. (2019). Missing Data Estimation Using Swarm Intelligence Algorithms from Reduced Dimensions. In: Deep Learning and Missing Data in Engineering Systems. Studies in Big Data, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-030-01180-2_9
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DOI: https://doi.org/10.1007/978-3-030-01180-2_9
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