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Tomoharu Nagao
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2020 – today
- 2022
- [c71]Tatsuaki Kobayashi
, Tomoharu Nagao
:
Comparison of Feature Selection Methods for Bottom-up of 1p/19q Co-deletion Prediction Performance in Grade 2 and 3 Gliomas. DMIP 2022: 77-82 - [c70]Masayuki Kobayashi, Shinichi Shirakawa, Tomoharu Nagao:
Auxiliary Data Selection in Percolative Learning Method for Improving Neural Network Performance. ICAART (3) 2022: 381-387 - [c69]Tatsuaki Kobayashi, Takafumi Haraguchi, Tomoharu Nagao:
Classifying the Presence or Absence of Calcifications on Mammography using the EfficientNet: A Feasibility Study. LifeTech 2022: 596-599 - [c68]Naoki Kuzuya, Tomoharu Nagao:
Designing B-spline-based Highly Efficient Neural Networks for IoT Applications on Edge Platforms. SMC 2022: 2305-2312 - 2021
- [c67]Satoshi Arai, Shinichi Shirakawa, Tomoharu Nagao:
Non-strict Attentional Region Annotation to Improve Image Classification Accuracy. SMC 2021: 2375-2380 - 2020
- [j13]Masanori Suganuma, Masayuki Kobayashi, Shinichi Shirakawa, Tomoharu Nagao:
Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming. Evol. Comput. 28(1): 141-163 (2020) - [c66]Masayuki Kobayashi, Tomoharu Nagao:
An evolution-based approach for efficient differentiable architecture search. GECCO Companion 2020: 131-132 - [c65]Masayuki Kobayashi, Tomoharu Nagao:
A Multi-objective architecture search for generative adversarial networks. GECCO Companion 2020: 133-134 - [c64]Yoshihisa Kanou, Tomoharu Nagao:
Separation of the Latent Representations into "Identity" and "Expression" without Emotional Labels. SMC 2020: 1638-1644 - [c63]Masayuki Kobayashi, Satoshi Arai, Tomoharu Nagao:
Evolutionary Generative Contribution Mappings. SMC 2020: 1657-1664 - [c62]Kazushi Motomura, Tomoharu Nagao:
Fishing Activity Prediction from Satellite Boat Detection Data. SMC 2020: 2870-2875 - [c61]Taro Kono, Satoshi Yamaguchi, Tomoharu Nagao:
Time Series Prediction with Dual Reliability: Uncertainty and Explainability. SMC 2020: 4095-4102 - [p1]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming. Deep Neural Evolution 2020: 185-208
2010 – 2019
- 2019
- [c60]Satoshi Yamaguchi, Kouzou Murakami, Chiaki Hirayama, Tomoharu Nagao:
Tumor Detection Method with Traceable Decision Process. SMC 2019: 3042-3047 - [c59]Chiaki Hirayama, Tomoharu Nagao:
Dynamic Path Costs Update Method reflecting Delivery Tendencies for Multi-Agent Delivery Tasks. SMC 2019: 4361-4366 - 2018
- [j12]Masayuki Kobayashi, Masanori Suganuma, Tomoharu Nagao:
A generative model approach for visualising convolutional neural networks. Int. J. Comput. Intell. Stud. 7(3/4): 214-230 (2018) - [c58]Kosaku Fujita, Masayuki Kobayashi, Tomoharu Nagao:
Data Augmentation using Evolutionary Image Processing. DICTA 2018: 1-6 - [c57]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. IJCAI 2018: 5369-5373 - [c56]Yuta Hasunuma, Chiaki Hirayama, Masayuki Kobayashi, Tomoharu Nagao:
Non-parallel Voice Conversion Using Generative Adversarial Networks. SMC 2018: 1635-1640 - [c55]Kazuki Takaishi, Masayuki Kobayashi, Miku Yanagimoto, Tomoharu Nagao:
Percolative Learning: Time-Series Prediction from Future Tendencies. SMC 2018: 1647-1652 - 2017
- [c54]Masayuki Kobayashi, Masanori Suganuma, Tomoharu Nagao:
Generative adversarial network for visualizing convolutional network. IWCIA 2017: 153-158 - [c53]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A genetic programming approach to designing convolutional neural network architectures. GECCO 2017: 497-504 - [c52]Miku Yanagimoto, Chika Sugimoto, Tomoharu Nagao:
Frequency filter networks for EEG-based recognition. SMC 2017: 270-275 - [c51]Chiaki Hirayama, Toshiya Watanabe, Shinji Kawabata, Masanori Suganuma, Tomoharu Nagao:
Acquiring grasp strategies for a multifingered robot hand using evolutionary algorithms. SMC 2017: 1597-1602 - [i1]Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao:
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures. CoRR abs/1704.00764 (2017) - 2016
- [j11]Shinichi Shirakawa
, Tomoharu Nagao:
Bag of local landscape features for fitness landscape analysis. Soft Comput. 20(10): 3787-3802 (2016) - [c50]Shinya Watanuki, Tomoharu Nagao:
Optimizing the structure of a path analysis model using a real-valued flexibly connected neural network. IWCIA 2016: 33-38 - [c49]Yusuke Natsui, Tomoharu Nagao:
Single frame super-resolution using multiple graph structured program. IWCIA 2016: 75-80 - [c48]Ken Shimazaki, Tomoharu Nagao:
Semantic segmentation using Three-Dimensional Cellular Evolutionary Networks. SMC 2016: 1411-1416 - [c47]Masanori Suganuma, Daiki Tsuchiya, Shinichi Shirakawa, Tomoharu Nagao:
Hierarchical feature construction for image classification using Genetic Programming. SMC 2016: 1423-1428 - 2015
- [c46]Ken Shimazaki, Tomoharu Nagao:
Semantic segmentation considering location and co-occurrence in scene. IWCIA 2015: 41-46 - [c45]Toshihiko Nishimura, Tomoharu Nagao, Hiroshi Iseki, Yoshihiro Muragaki, Manabu Tamura, Shinji Minami:
Construction of annotated data for analysis of recorded cortical mapping videos. IWCIA 2015: 65-70 - 2014
- [c44]Junji Otsuka, Tomoharu Nagao:
Evolutionary Fuzzy Rule Construction for Iterative Object Segmentation. ICAART (1) 2014: 84-93 - [c43]Shinichi Shirakawa, Tomoharu Nagao:
Local Landscape Patterns for Fitness Landscape Analysis. SEAL 2014: 467-478 - [c42]Toshihiko Nishimura, Tomoharu Nagao, Hiroshi Iseki, Yoshihiro Muragaki, Manabu Tamura, Shinji Minami:
Automatic video tagging method for cortical mapping in awake craniotomy records. SMC 2014: 2637-2642 - 2013
- [c41]Toshihiko Nishimura, Tomoharu Nagao
:
Detecting electrical stimulation of cortical mapping from recorded awake surgery sounds. IWCIA 2013: 101-106 - [c40]Masanori Suganuma, Tomoharu Nagao
:
Detection of electrical stimulation position in recorded surgery videos of cortical mapping in awake brain surgery. IWCIA 2013: 131-136 - [c39]Yusuke Natsui, Tomoharu Nagao
:
Automatic construction of single frame super-resolution using Cartesian Genetic Programming. IWCIA 2013: 149-154 - [c38]Ken Shimazaki, Tomoharu Nagao
:
Scene classification using color and structure-based features. IWCIA 2013: 211-216 - [c37]Keita Nakayama, Tomoharu Nagao
:
Automatic Construction of Image Transformations to Produce Variously Stylized Painterly Images. EMS 2013: 243-248 - [c36]Tomohiro Nagata, Tomoharu Nagao:
Disparity Diffusion/Absorption-Based Stereo Matching Using Cellular Evolutionary Neural Network with Initial Disparity Optimization. SMC 2013: 858-863 - [c35]Ryoji Ohira, Noriko Yata, Tomoharu Nagao
:
A Classification System for Gray Scale Images by Using Combination of Simple Figures. SMC 2013: 1187-1192 - [c34]Kota Saito, Tomoharu Nagao
:
A Self-Organizing Method Using Data Movement on Spherical Surface. SMC 2013: 1193-1198 - [c33]Junji Otsuka, Tomoharu Nagao
:
An Improvement in Classification Accuracy of Fuzzy Oriented Classifier Evolution. SMC 2013: 3921-3926 - 2012
- [c32]Noriko Yata, Tomoharu Nagao, Keiji Uchikawa:
Dichromat's Categorical Color Perception Model. CGIV 2012: 295-300 - [c31]Junji Otsuka, Tomoharu Nagao
:
Flexible design of image classification rules using extended Fuzzy Oriented Classifier Evolution. SCIS&ISIS 2012: 1595-1600 - 2010
- [c30]Yuta Nakano, Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao
:
Automatic construction of image transformation algorithms using feature based genetic image network. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c29]Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao
:
Evolving search spaces to emphasize the performance difference of real-coded crossovers using genetic programming. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c28]Shiro Nakayama, Shinichi Shirakawa, Noriko Yata, Tomoharu Nagao:
Ensemble Image Classification Method Based on Genetic Image Network. EuroGP 2010: 313-324 - [c27]Chalothorn Liewchavalit, Masakazu Akiba, Tsuneo Kanno, Tomoharu Nagao
:
Extracted facial feature of racial closely related faces. ICDIP 2010: 75461R - [c26]Haiying Bai, Noriko Yata, Tomoharu Nagao
:
Efficient evolutionary image processing using genetic programming: Reducing computation time for generating feature images of the Automatically Construction of Tree-Structural Image Transformation (ACTIT). ISDA 2010: 302-307
2000 – 2009
- 2009
- [c25]Shinichi Shirakawa, Tomoharu Nagao
:
Evolutionary image segmentation based on multiobjective clustering. IEEE Congress on Evolutionary Computation 2009: 2466-2473 - [c24]Shinichi Shirakawa, Tomoharu Nagao
:
Evolution of Search Algorithms Using Graph Structured Program Evolution. EuroGP 2009: 109-120 - [c23]Shinichi Shirakawa, Shiro Nakayama, Tomoharu Nagao
:
Genetic Image Network for Image Classification. EvoWorkshops 2009: 395-404 - [c22]Shinichi Shirakawa, Tomoharu Nagao
:
Graph structured program evolution with automatically defined nodes. GECCO 2009: 1107-1114 - [c21]Jun Ando, Tomoharu Nagao
:
Image Classification and Processing using Modified Parallel-ACTIT. SMC 2009: 1787-1791 - 2008
- [c20]Shinichi Shirakawa, Tomoharu Nagao:
Evolutionary algorithm considering program size: efficient program evolution using grape. GECCO (Companion) 2008: 2217-2222 - [c19]Hiroaki Nishihara, Tomoharu Nagao
:
Extraction of Illumination Effects from Natural Images with Color Transition Model. ISVC (2) 2008: 752-761 - 2007
- [j10]Genya Ogawa, Katsuyuki Kise, Tsuyoshi Torii, Tomoharu Nagao
:
Onboard Evolutionary Risk Recognition System for Automobiles - Toward the Risk Map System. IEEE Trans. Ind. Electron. 54(2): 878-886 (2007) - [c18]Shinichi Shirakawa, Shintaro Ogino, Tomoharu Nagao
:
Graph structured program evolution. GECCO 2007: 1686-1693 - [c17]Shinichi Shirakawa, Tomoharu Nagao:
Feed Forward Genetic Image Network: Toward Efficient Automatic Construction of Image Processing Algorithm. ISVC (2) 2007: 287-297 - [c16]Osamu Hirose, Tomoharu Nagao:
Anisotropic Potential Field Maximization Model for Subjective Contour from Line Figure. ISVC (1) 2007: 310-320 - [c15]Yuta Nakano, Tomoharu Nagao
:
Automatic construction of moving object segmentation from video image using 3D-ACTIT. SMC 2007: 1153-1158 - [c14]Shinichi Shirakawa, Tomoharu Nagao
:
Evolution of sorting algorithm using graph structured program evolution. SMC 2007: 1256-1261 - [c13]Jun Ando, Tomoharu Nagao
:
Fast evolutionary image processing using Multi-GPUs. SMC 2007: 2927-2932 - 2005
- [c12]Shumei Liu, Tomoharu Nagao:
Adaptive XCSM for Perceptual Aliasing Problems. ICNC (3) 2005: 566-571 - 2004
- [j9]Yi Hu, Tomoharu Nagao:
A Template Matching Method Based on Marker-Controlled Watershed Segmentation. IEICE Trans. Inf. Syst. 87-D(10): 2389-2398 (2004) - [c11]Shintaro Ogino, Tomoharu Nagao
:
The Chaos Analysis of Long Memory Process in Artificial Stock Markets Consist of Multi-Agents. CW 2004: 249-253 - [c10]Yi Hu, Tomoharu Nagao
:
A matching method based on marker-controlled watershed segmentation. ICIP 2004: 283-286 - 2003
- [c9]Yi Hu, Tomoharu Nagao
:
Matching of characters in scene images by using local shape feature vectors. ICIAP 2003: 207-212 - 2002
- [j8]Akira Hara, Tomoharu Nagao:
Construction and Analysis of Stock Market Model Using ADG; Automatically Defined Groups. Int. J. Comput. Intell. Appl. 2(4): 433-446 (2002) - [j7]Daisuke Hiratsu, Tomoharu Nagao:
A proposal of 2D artificial cellular neural network including nonvolatile unit. Syst. Comput. Jpn. 33(7): 40-49 (2002)
1990 – 1999
- 1999
- [c8]Akira Hara, Tomoharu Nagao:
Emergence of the cooperative behavior using ADG; Automatically Defined Groups. GECCO 1999: 1039-1046 - [c7]Shinya Aoki, Tomoharu Nagao
:
Automatic Construction of Tree-Structural Image Transformations Using Genetic Programming. ICIAP 1999: 136-141 - [c6]Shinya Aoki, Tomoharu Nagao:
Automatic Construction of Tree-Structural Image Transformation Using Genetic Programming. ICIP (1) 1999: 529-533 - 1996
- [c5]Tomoharu Nagao:
Homogeneous Coding for Genetic Algorithm Based Parameter Optimization. International Conference on Evolutionary Computation 1996: 426-430 - [c4]Tomoharu Nagao, Shinya Masunaga:
Automatic construction of image transformation processes using genetic algorithm. ICIP (3) 1996: 731-734 - 1993
- [c3]Tomoharu Nagao
, Takeshi Agui, Hiroshi Nagahashi:
Extraction of two-dimensional arbitrary shapes using a genetic algorithm. VCIP 1993 - 1992
- [c2]Yan Jiafeng, Ban Cen Cao Qing, Takeshi Agui, Tomoharu Nagao:
The use of complex transform for extraction circular arcs and straight lines in engineering drawings. ICPR (3) 1992: 290-293 - 1990
- [j6]Takeshi Agui, Tomoharu Nagao, Hitoshi Misawa, Masayuki Nakajima:
A Data Management Method for Maps Using Band Division of Data Plane. Syst. Comput. Jpn. 21(2): 65-73 (1990) - [j5]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
A Method of Extracting Similar Figures Using Polar Features. Syst. Comput. Jpn. 21(3): 66-75 (1990) - [j4]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
An extraction method for same figure using polar features. Syst. Comput. Jpn. 21(8): 72-81 (1990) - [j3]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
Automatic extraction of roads denoted by parallel lines from 1/25, 000-scaled maps utilizing skip-scan method. Syst. Comput. Jpn. 21(11): 96-105 (1990) - [c1]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
Extraction of arbitrary shapes from a noisy binary image using pseudo view field tracer. VCIP 1990
1980 – 1989
- 1987
- [j2]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
An identification method of closed regions between line drawings using motion analysis. Syst. Comput. Jpn. 18(7): 46-56 (1987) - 1986
- [j1]Tomoharu Nagao, Takeshi Agui, Masayuki Nakajima:
A region extraction method using a distance function between images. Syst. Comput. Jpn. 17(5): 75-83 (1986)
Coauthor Index
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