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ORCIDMotohisa Fukuda
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2020 – today
- 2023
[i2]Motohisa Fukuda:
Symbolically integrating tensor networks over various random tensors by the second version of Python RTNI. CoRR abs/2309.01167 (2023)- 2021
- [j7]Yago Diez
, Sarah Kentsch, Motohisa Fukuda, Maximo Larry Lopez Caceres, Koma Moritake, Mariano Cabezas:
Deep Learning in Forestry Using UAV-Acquired RGB Data: A Practical Review. Remote. Sens. 13(14): 2837 (2021) - [j6]Motohisa Fukuda, Takashi Okuno, Shinya Yuki:
Central Object Segmentation by Deep Learning to Continuously Monitor Fruit Growth through RGB Images. Sensors 21(21): 6999 (2021) - 2020
- [i1]Motohisa Fukuda, Takashi Okuno, Shinya Yuki:
Central object segmentation by deep learning for fruits and other roundish objects. CoRR abs/2008.01251 (2020)
2010 – 2019
- 2018
- [j5]Motohisa Fukuda, Ion Nechita:
On the Minimum Output Entropy of Random Orthogonal Quantum Channels. IEEE Trans. Inf. Theory 64(2): 1374-1384 (2018) - 2017
- [j4]Motohisa Fukuda, Gilad Gour:
Additive Bounds of Minimum Output Entropies for Unital Channels and an Exact Qubit Formula. IEEE Trans. Inf. Theory 63(3): 1818-1828 (2017) - 2015
- [j3]Motohisa Fukuda, Ion Nechita, Michael M. Wolf:
Quantum Channels With Polytopic Images and Image Additivity. IEEE Trans. Inf. Theory 61(4): 1851-1859 (2015)
2000 – 2009
- 2007
- [j2]Motohisa Fukuda:
Simplification of Additivity Conjecture in Quantum Information Theory. Quantum Inf. Process. 6(3): 179-186 (2007) - 2006
- [j1]Nilanjana Datta, Motohisa Fukuda, Alexander S. Holevo:
Complementarity and Additivity for Covariant Channels. Quantum Inf. Process. 5(3): 179-207 (2006)
Coauthor Index
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