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References

1 
Schmidhuber J., 2015, Deep Learning in Neural Networks: An Overview, Neural Networks, Vol. 61, pp. 85-117DOI
2 
LeCun Y., Bengio Y., Hinton G., 2015, Deep learning, Nature, Vol. 521, pp. 436-444Google Search
3 
Goldberg J. D., 1989, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MAGoogle Search
4 
Stanley K. O., Miikkulainen R., 2004, Competitive coevolution through evolutionary complexification, Journal of Artificial Intelligence Research, Vol. 21, No. , pp. 63-100DOI
5 
Stanley K. O., D’Ambrosio D. B., Gauci J., 2009, A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks, Artificial Life, Vol. 15, No. 2, pp. 185-212DOI
6 
Stanley K. O., 2007, Compositional pattern producing networks: A novel abstraction of development, Genetic Programming and Evolvable Machines Special Issue on Dev. Sys., Vol. 8, No. 2, pp. 131-162DOI
7 
Fernando C., 2016, Convolution by Evolution: Differentiable Pattern Producing Networks, In Proceedings of the 2016 Genetic and Evolutionary Computation Conference, Denver, CO, USA, pp. 109-116DOI
8 
Rikhtegar A., Pooyan M., Manzuri-Shalmani M., 2016, Genetic algorithm-optimised structure of convolutional neural network for face recognition applications, IET Computer Vision, Vol. 10, No. 6, pp. 559-566DOI
9 
Xie L., Yuille A., Genetic CNN, CVPR 2017DOI
10 
Suganuma M., Shirakawa S., Nagao T., 2017, A Genetic Programming Approach to Designing Convolutional Neural Network Architectures, Proceedings of GECCO 2017, pp. 497-504DOI
11 
LeCun , Yann , 1998, Gradient-based learning applied to document recognition, Proceedings of the IEEE, pp. 2278-2324DOI
12 
Koza J. R., 1992, Genetic Programming: On the Programming of Computers by Means of Natural Selection, The MIT PressGoogle Search
13 
Miller J., Thomson P., 2000, Cartesian Genetic Programming, EuroGP 2000. LNCS, Springer, Vol. 1802, pp. 121-132DOI
14 
Simonyan K., Zisserman A., 2014, Very Deep Convolutional Networks for Large-Scale Image Recognition, International Conference on Learning RepresentationsGoogle Search
15 
Szegedy C., Liu W., Jia Y., Sermanet P., Reed S., Anguelov D., Erhan D., Vanhoucke V., Rabinovich A., 2015, Going Deeper with Convolutions, Computer Vision and Pattern RecognitionDOI
16 
He K., Zhang X., Ren S., Sun J., 2016, Deep Residual Learning for Image Recognition, Computer Vision and Pattern RecognitionDOI
17 
Zagoruyko S., Komodakis N., 2016, Wide Residual Networks, arXiv: 1605.07146Google Search
18 
Xie L., Wang J., Lin W., Zhang B., Tian Q., 2016, Towards Reversal-Invariant Image Representation, International Journal on Computer VisionDOI
19 
Simonyan K., Zisserman A., 2014, Very Deep Convolutional Networks for Large-Scale Image Recognition, International Conference on Learning RepresentationsGoogle Search
20 
He K., Zhang X., Ren S., Sun J., 2016, Deep Residual Learning for Image Recognition, Computer Vision and Pattern RecognitionDOI
21 
Huang G., Liu Z., Weinberger K., 2016, Densely Connected Convolutional Networks, arXiv: 1608.06993DOI