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Nagao, Tomoharu
117  Ergebnisse:
Personensuche X
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1

MIPCE: Generating Multiple Patches Counterfactual-Changing ..:

, In: Artificial Neural Networks and Machine Learning – ICANN 2023; Lecture Notes in Computer Science,
Okumura, Hiroyuki ; Nagao, Tomoharu - p. 231-242 , 2023
Link: https://doi.org/10.1007/..
 
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2

Comparison of Feature Selection Methods for Bottom-up of 1p..:

, In: Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing,
Kobayashi, Tatsuaki ; Nagao, Tomoharu - p. 77-82 , 2022
Link: https://dl.acm.org/doi/1..
 
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3

Designing B-spline-based Highly Efficient Neural Networks f..:

, In: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Kuzuya, Naoki ; Nagao, Tomoharu - p. 2305-2312 , 2022
Link: https://doi.org/10.1109/..
 
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4

Classifying presence or absence of calcifications on mammog..:

Kobayashi, Tatsuaki ; Haraguchi, Takafumi ; Nagao, Tomoharu
Radiological Physics and Technology.  15 (2022)  4 - p. 340-348 , 2022
Link: https://doi.org/10.1007/..
 
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5

Classifying the Presence or Absence of Calcifications on Ma..:

, In: 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech),
Kobayashi, Tatsuaki ; Haraguchi, Takafumi ; Nagao, Tomoharu - p. 596-599 , 2022
Link: https://doi.org/10.1109/..
 
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6

Time Series Prediction with Dual Reliability: Uncertainty a..:

, In: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Kono, Taro ; Yamaguchi, Satoshi ; Nagao, Tomoharu - p. 4095-4102 , 2020
Link: https://doi.org/10.1109/..
 
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7

Fishing Activity Prediction from Satellite Boat Detection D..:

, In: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Motomura, Kazushi ; Nagao, Tomoharu - p. 2870-2875 , 2020
Link: https://doi.org/10.1109/..
 
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8

Designing Convolutional Neural Network Architectures Using ..:

, In: Natural Computing Series; Deep Neural Evolution,
Suganuma, Masanori ; Shirakawa, Shinichi ; Nagao, Tomoharu - p. 185-208 , 2020
Link: https://doi.org/10.1007/..
 
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9

Evolution of Deep Convolutional Neural Networks Using Carte..:

Suganuma, Masanori ; Kobayashi, Masayuki ; Shirakawa, Shinichi.
Evolutionary Computation.  28 (2020)  1 - p. 141-163 , 2020
Link: https://doi.org/10.1162/..
 
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10

A Multi-objective architecture search for generative advers..:

, In: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion,
Kobayashi, Masayuki ; Nagao, Tomoharu - p. 133-134 , 2020
Link: https://dl.acm.org/doi/1..
 
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11

Evolutionary Generative Contribution Mappings:

, In: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Kobayashi, Masayuki ; Arai, Satoshi ; Nagao, Tomoharu - p. 1657-1664 , 2020
Link: https://doi.org/10.1109/..
 
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12

Separation of the Latent Representations into "Identity" an..:

, In: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Kanou, Yoshihisa ; Nagao, Tomoharu - p. 1638-1644 , 2020
Link: https://doi.org/10.1109/..
 
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13

An evolution-based approach for efficient differentiable ar..:

, In: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion,
Kobayashi, Masayuki ; Nagao, Tomoharu - p. 131-132 , 2020
Link: https://dl.acm.org/doi/1..
 
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14

Tumor Detection Method with Traceable Decision Process:

, In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC),
Yamaguchi, Satoshi ; Murakami, Kouzou ; Hirayama, Chiaki. - p. 3042-3047 , 2019
Link: https://doi.org/10.1109/..
 
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15

Dynamic Path Costs Update Method reflecting Delivery Tenden..:

, In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC),
Hirayama, Chiaki ; Nagao, Tomoharu - p. 4361-4366 , 2019
Link: https://doi.org/10.1109/..
 
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