Genetic Programming Bibliography entries for Masanori Suganuma

up to index Created by W.Langdon from gp-bibliography.bib Revision:1.8129

GP coauthors/coeditors: Daiki Tsuchiya, Shinichi Shirakawa, Tomoharu Nagao, Masayuki Kobayashi,

Genetic Programming Articles by Masanori Suganuma

• Masanori Suganuma and Masayuki Kobayashi and Shinichi Shirakawa and Tomoharu Nagao. Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming. Evolutionary Computation, 28(1):141-163, 2020. details

Genetic Programming PhD doctoral thesis Masanori Suganuma

• Masanori Suganuma. A Study on Salient Event Detection in Videos. PhD thesis, Information Media and Environment Sciences, Graduate School of Environment and Information Sciences, Yokohama National University, 79-7 Tokiwadai, Hodogaya-ku, Yokohama 240-8501, Japan, 2017. details

Genetic Programming conference papers by Masanori Suganuma

• Masanori Suganuma and Shinichi Shirakawa and Tomoharu Nagao. A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. In Jerome Lang editor, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, pages 5369-5373, 2018. International Joint Conferences on Artificial Intelligence Organization. details

• Masanori Suganuma and Shinichi Shirakawa and Tomoharu Nagao. A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 497-504, Berlin, Germany, 2017. ACM. details

• Masanori Suganuma and Daiki Tsuchiya and Shinichi Shirakawa and Tomoharu Nagao. Hierarchical feature construction for image classification using Genetic Programming. In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 001423-001428, 2016. details

Genetic Programming book chapters by Masanori Suganuma

• Masanori Suganuma and Shinichi Shirakawa and Tomoharu Nagao. Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming. In Hitoshi Iba and Nasimul Noman editors, Deep Neural Evolution: Deep Learning with Evolutionary Computation, chapter 7, pages 185-208. Springer, Singapore, 2020. details