A Case Study of Generative Adversarial Networks for Procedural Synthesis of Original Textures in Video Games
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[1] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[2] Amin Mansouri,et al. Metaheuristic neural networks for anomaly recognition in industrial sensor networks with packet latency and jitter for smart infrastructures , 2018, International Journal of Computers and Applications.
[3] Julian Togelius,et al. Procedural Content Generation via Machine Learning (PCGML) , 2017, IEEE Transactions on Games.
[4] Jinchuan Zheng,et al. Modular interpretation of low altitude aerial images of non-urban environment , 2014, Digit. Signal Process..
[5] Julian Togelius,et al. Procedural Content Generation in Games , 2016, Computational Synthesis and Creative Systems.
[6] Leon A. Gatys,et al. Texture Synthesis Using Convolutional Neural Networks , 2015, NIPS.
[7] Babak Majidi,et al. Deep cross altitude visual interpretation for service robotic agents in smart city , 2018, 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS).
[8] Babak Majidi,et al. Glimpse-gaze deep vision for Modular Rapidly Deployable Decision Support Agent in smart jungle , 2018, 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS).
[9] Mohammad Eshghi,et al. A deep residual neural network for low altitude remote sensing image classification , 2018, 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS).
[10] V. K. Vashistha,et al. Procedural Content Generation in Games towards Semantic Web , 2018 .