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2020 – today
- 2024
[j7]Luan Thanh Trinh
, Tomoki Hamagami:
Latent Denoising Diffusion GAN: Faster Sampling, Higher Image Quality. IEEE Access 12: 78161-78172 (2024)- [j6]Hayato Nakagawa, Takuro Fujii, Yasushi Yumura, Tomoki Hamagami:
Estimation of Multi-Expert Sperm Assessments Using Video Recognition Based Model Trained by EMD Loss. IEEE Access 12: 112702-112713 (2024) - [j5]Luan Thanh Trinh, Tomoki Hamagami, Naoya Okamoto:
3D Ship Hull Design Direct Optimization Using Generative Adversarial Network. J. Adv. Comput. Intell. Intell. Informatics 28(3): 693-703 (2024) - [c27]Takuro Fujii, Hayato Nakagawa, Teppei Takeshima, Yasushi Yumura, Tomoki Hamagami:
Automated Sperm Assessment Framework and Neural Network Specialized for Sperm Video Recognition. WACV 2024: 7660-7669 - [i3]Luan Thanh Trinh, Tomoki Hamagami:
Latent Denoising Diffusion GAN: Faster sampling, Higher image quality. CoRR abs/2406.11713 (2024) - [i2]Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami:
Test-time Adaptation for Regression by Subspace Alignment. CoRR abs/2410.03263 (2024) - 2023
- [j4]Yoshiyuki Tajima, Tomoki Hamagami:
Ordinal Regression Based on the Distributional Distance for Tabular Data. IEICE Trans. Inf. Syst. 106(3): 357-364 (2023) - [i1]Takuro Fujii, Hayato Nakagawa, Teppei Takeshima, Yasushi Yumura, Tomoki Hamagami:
Automated Sperm Assessment Framework and Neural Network Specialized for Sperm Video Recognition. CoRR abs/2311.05927 (2023) - 2022
- [j3]Kodai Yamashita, Tomoki Hamagami:
Reinforcement Learning for POMDP Environments Using State Representation with Reservoir Computing. J. Adv. Comput. Intell. Intell. Informatics 26(4): 562-569 (2022) - 2021
- [c26]Yoshiyuki Tajima, Tomoki Hamagami:
Ordinal Regression Based on the Distributional Distance Between Labels. SMC 2021: 1482-1488 - 2020
- [c25]Koichi Iwai, Masanori Akiyoshi, Tomoki Hamagami:
Structured Feature Derivation for Transfer Learning on Credit Scoring. SMC 2020: 818-823
2010 – 2019
- 2019
- [c24]Kundo Lee, Tomoki Hamagami:
Block-Based Neural Network High Speed Optimization. IES 2019: 79-92 - [c23]Xin Li, Tomoki Hamagami:
An Improved Auto-encoder Based on 2-Level Prioritized Experience Replay for High Dimension Skewed Data. IES 2019: 93-105 - 2018
- [c22]Masaya Nakata, Will N. Browne, Tomoki Hamagami:
Theoretical adaptation of multiple rule-generation in XCS. GECCO 2018: 482-489 - [c21]Kundo Lee, Tomoki Hamagami:
Performance Oriented Block-Based Neural Network Model by Parallelized Neighbor's Communication. SMC 2018: 1623-1628 - [c20]Hayato Sasaki, Masaya Nakata, Mizuki Yamamoto, Teppei Takeshima, Yasushi Yumura, Tomoki Hamagami:
Investigation about Control of False Positive Rate for Automatic Sperm Detection in Assisted Reproductive Technology. SMC 2018: 1964-1969 - 2017
- [j2]Masaya Nakata, Tomoki Hamagami:
An Analysis of Rule Deletion Scheme in XCS on Reinforcement Learning Problem. J. Adv. Comput. Intell. Intell. Informatics 21(5): 876-884 (2017) - [c19]Masaya Nakata, Will N. Browne, Tomoki Hamagami, Keiki Takadama:
Theoretical XCS parameter settings of learning accurate classifiers. GECCO 2017: 473-480 - [c18]Hayato Sasaki, Masaya Nakata, Fumiya Hamatsu, Tomoki Hamagami:
Effect of parameter sharing for multimodal deep autoencoders. SMC 2017: 1966-1971 - 2014
- [c17]Takuo Suzuki, Tomoki Hamagami:
Context awareness by unit-type evolutionary Petri net for team medical care support. SMC 2014: 385-390 - 2012
- [j1]Hongbo Shi, Tomoki Hamagami, Haoyuan Xu, Ping Yu, Yonghe Wu:
A Method for Classifying Packets into Network Flows Based on GHSOM. Mob. Networks Appl. 17(6): 730-739 (2012) - [c16]Mitsuhiro Nakamura, Tomoki Hamagami:
A Software Quality Evaluation Method Using the Change of Source Code Metrics. ISSRE Workshops 2012: 65-69 - 2011
- [c15]Hongbo Shi, Tomoki Hamagami, Haoyuan Xu:
Machine Learning Based Autonomous Network Flow Identifying Method. WICON 2011: 447-457 - 2010
- [c14]Takeshi Shibuya, Hideaki Arita, Tomoki Hamagami:
Reinforcement learning in continuous state space with perceptual aliasing by using complex-valued RBF network. SMC 2010: 1799-1803 - [c13]Atsuhiro Yamazaki, Tomoki Hamagami, Takeshi Shibuya:
Complex-valued reinforcement learning with hierarchical architecture. SMC 2010: 1925-1931
2000 – 2009
- 2009
- [c12]Hongbo Shi, Tomoki Hamagami:
Cross-Layer Routing Method for the SCTP with Multihoming MIPv6. AccessNets 2009: 179-191 - 2007
- [c11]Manabu Kominami, Tomoki Hamagami:
A new genetic algorithm with diploid chromosomes by using probability decoding for non-stationary function optimization. SMC 2007: 1268-1273 - [c10]Takeshi Shibuya, Shingo Shimada, Tomoki Hamagami:
Experimental study of the eligibility traces in complex valued reinforcement learning. SMC 2007: 1630-1635 - 2006
- [c9]Tomoki Hamagami, Takeshi Shibuya, Shingo Shimada:
Complex-Valued Reinforcement Learning. SMC 2006: 4175-4179 - 2005
- [c8]Tomoki Hamagami, Hironori Hirata:
State space partitioning and clustering with sensor alignment for autonomous robots. SMC 2005: 2655-2660 - 2004
- [c7]Tomoki Hamagami, Hironori Hirata:
Development of intelligent wheelchair acquiring autonomous, cooperative, and collaborative behavior. SMC (4) 2004: 3525-3530 - 2003
- [c6]Tomoki Hamagami, Hironori Hirata:
Method of crowd simulation by using multiagent on cellular automata. IAT 2003: 46-52 - [c5]Tomoki Hamagami, Hironori Hirata:
An adjustment method of the number of states of Q-learning segmenting state space adaptively. SMC 2003: 3062-3067
1990 – 1999
- 1996
- [c4]Ken-ichi Magata, Tomoki Hamagami, Mitsuo Komura:
A method for estimating prosodic symbol from text for Japanese text-to-speech synthesis. ICSLP 1996: 1373-1376 - [c3]Tomoki Hamagami, Ken-ichi Magata, Mitsuo Komura:
A study on Japanese prosodic pattern and its modeling in restricted speech. ICSLP 1996: 1628-1631 - 1990
- [c2]Tomoki Hamagami, Shinichiro Hashimoto:
The improved source model for high-quality synthetic speech sound. ICSLP 1990: 805-808 - [c1]Tomoki Hamagami, Shinichiro Hashimoto:
A new synthesizer model for high quality synthetic speech. SSW 1990: 59-62
Coauthor Index
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last updated on 2024-11-13 23:52 CET by the dblp team
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