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MGGAN: improving sample generations of Generative Adversarial Networks
Version 2 2024-06-06, 01:33
Version 1 2022-10-12, 01:29
conference contribution
posted on 2024-06-06, 01:33 authored by H Wu, L He, Chang-Tsun LiChang-Tsun Li, J Li, W Wu, C MapleMGGAN: improving sample generations of Generative Adversarial Networks
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Pagination
369-376Location
Haikou, Hainan, ChinaStart date
2021-12-20End date
2021-12-22ISBN-13
9781665494571Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
Proceedings: 2021 IEEE 23rd International Conference on High Performance Computing and Communications, 7th International Conference on Data Science and Systems, 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021Event
2021 IEEE 23rd International Conference on High Performance Computing & Communications; 7th Internatinal Conference on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)Publisher
Institute of Electrical and Electronics EngineersPlace of publication
Piscataway, N.J.Usage metrics
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