Kunihiko Fukushima

发表

Modeling Neural Networks for Artificial Vision

Kunihiko Fukushima, K. Fukushima, 2006 .

Bistability of mixed states in a neural network storing hierarchical patterns

Yoshiyuki Kabashima, Kunihiko Fukushima, Kaname Toya, 2000 .

Self-organization of shift-invariant receptive fields

Kunihiko Fukushima, K. Fukushima, K. Yoshimoto, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Recognition of occluded patterns: a neural network model

Kunihiko Fukushima, K. Fukushima, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Self-organization of shift-invariant receptive fields

Kunihiko Fukushima, K. Fukushima, Kazuya Yoshimoto, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Invariant pattern recognition with eye movement: A neural network model

Masayuki Kikuchi, Kunihiko Fukushima, K. Fukushima, 2001, Neurocomputing.

Interpolating vectors for robust pattern recognition

Kunihiko Fukushima, K. Fukushima, 2007, Neural Networks.

A neural network model for associative recall of maps

Yoshio Yamaguchi, Masato Okada, Kunihiko Fukushima, 1998, Systems and Computers in Japan.

Extraction of visual motion and optic flow

Kunihiko Fukushima, K. Fukushima, 2007, Neural Networks.

A neural network model extracting features from speech signals

Takayuki Ito, Kunihiko Fukushima, 1988, Systems and Computers in Japan.

Realization of a Neural Network Model Neocognitron on a Hypercube Parallel Computer

Takayuki Ito, Kunihiko Fukushima, Sei Miyake, 1990, Int. J. High Speed Comput..

Neural Network Model for Extracting Optic Flow

Kunihiko Fukushima, K. Fukushima, K. Tohyama, 2005, ICANN.

Margined Winner-Take-All: New learning rule for pattern recognition

Kunihiko Fukushima, K. Fukushima, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

2-1 Image Processing by Computer (2. Electronics in Image Processing) ( Electronic Image Technology)

Kunihiko Fukushima, K. Fukushima, 1972 .

Neocognitoron with New Mechanism of Bend-detector

Hayaru Shouno, Kunihiko Fukushima, Eiji Kimura, 1998 .

Cognitron: A self-organizing multilayered neural network

Kunihiko Fukushima, K. Fukushima, 1975, Biological Cybernetics.

Improved generalization ability using constrained neural network architectures

Kunihiko Fukushima, K. Fukushima, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Speed Invariant Speech Recognition Recognition Using Variable Velocity Delay-Lines

Kunihiko Fukushima, Kouichirou Yamauchi, Megumn Fukuda, 1994 .

ALPHANUMERIC CHARACTER RECOGNITION BY THE NEOCOGNITRON

Kunihiko Fukushima, Nobuaki Wake, K. Fukushima, 1990 .

Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position

Kunihiko Fukushima, Sei Miyake, K. Fukushima, 1982, Pattern Recognit..

Recognition and Segmentation of Components of a Face by a Multi-Resolution Neural Network

Hideki Hashimoto, Kunihiko Fukushima, K. Fukushima, 1997, ICANN.

Use of non-uniform spatial blur for image comparison: symmetry axis extraction

Kunihiko Fukushima, K. Fukushima, 2005, Neural Networks.

How to adjust the thresholds of feature-extracting cells in the neocognitron

Masashi Tanigawa, Kunihiko Fukushima, K. Fukushima, 1994, Systems and Computers in Japan.

Modeling Vision with the Neocognitron

Kunihiko Fukushima, K. Fukushima, 2014 .

Recognition of Handwritten Digits in the Real World by a Neocognitron

Masato Okada, Hayaru Shouno, Kunihiko Fukushima, 1999, KNOWLEDGE-BASED INTELLIGENT TECHNIQUES in CHARACTER RECOGNITION.

Introduction

Diego Andina, Kunihiko Fukushima, Francisco Javier Ropero Peláez, 2018, Int. J. Neural Syst..

A Neural Network Model for Detecting the Motion of an Object Whose Vertexes are Masked

Masayuki Kikuchi, Kunihiko Fukushima, H. Matsuda, 1997, ICONIP.

Robust Pattern Recognition by Interpolating Vectors

Kunihiko Fukushima, K. Fukushima, 2007, 2007 International Joint Conference on Neural Networks.

ネオコグニトロン：Deep Convolutional Neural Network

Kunihiko Fukushima, K. Fukushima, 2015 .

Neocognitron with improved bend-extractors: Recognition of handwritten digits in the real world

Hayaru Shouno, Kunihiko Fukushima, Eiji Kimura, 1998, Neural Computing & Applications.

Neural Networks for Visual Pattern Recognition

Kunihiko Fukushima, K. Fukushima, 1991 .

Active and Adaptive Vision: Neural Network Models

Kunihiko Fukushima, K. Fukushima, 2000, Biologically Motivated Computer Vision.

Recognition and segmentation of facial components using selective attention mechanism

Hideki Hashimoto, Kunihiko Fukushima, K. Fukushima, 1999, Systems and Computers in Japan.

Neocognitron capable of incremental learning

Kunihiko Fukushima, 2004, Neural Networks.

Recognition and segmentation of facial components using selective attention mechanism

Hideki Hashimoto, Kunihiko Fukushima, K. Fukushima, 1999, Systems and Computers in Japan.

Deep convolutional network neocognitron: Improved Interpolating-Vector

Hayaru Shouno, Kunihiko Fukushima, K. Fukushima, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A neural network model for associative recall of maps

Masato Okada, Y. Yamaguchi, Kunihiko Fukushima, 1998 .

Neocognitron with dual C-cell layers

Masato Okada, Kunihiko Fukushima, Kazuhito Hiroshige, 1994, Neural Networks.

Character recognition with neural networks

Kunihiko Fukushima, K. Fukushima, 1992, Neurocomputing.

Neocognitron: A hierarchical neural network capable of visual pattern recognition

Kunihiko Fukushima, K. Fukushima, 1988, Neural Networks.

Feature Extractor for Pattern Recognizer and Animal's Visual System

Kunihiko Fukushima, 1968 .

Self-Organization of a Neural Network which Gives Position-Invariant Response

Kunihiko Fukushima, 1979, IJCAI.

A Probabilistic WKL Rule for Incremental Feature Learning and Pattern Recognition

Isao Hayashi, Kunihiko Fukushima, Jasmin Léveillé, 2014, J. Adv. Comput. Intell. Intell. Informatics.

Increasing robustness against background noise: Visual pattern recognition by a neocognitron

Kunihiko Fukushima, K. Fukushima, 2011, Neural Networks.

Neocognitron of a New Version: Handwritten Digit Recognition

Kunihiko Fukushima, 2001, ICANN.

Correction to "Visual Feature Extraction by a Multilayered Network of Analog Threshold Elements"

Kunihiko Fukushima, K. Fukushima, 1970, IEEE Transactions on Systems Science and Cybernetics.

Training neocognitron to recognize handwritten digits in the real world

Hayaru Shouno, Kunihiko Fukushima, K. Nagahara, 1997, Proceedings of IEEE International Symposium on Parallel Algorithms Architecture Synthesis.

A Stereo Algorithm with Occlusion Constraint

Osamu Watanabe, Kunihiko Fukushima, K. Fukushima, 1997 .

A speech recognition system consisting of auditory feature extraction cells and velocity-controlled delay-lines. I. Feature extraction module

Kunihiko Fukushima, Mitsuhiro Fukuda, Koichiro Yamauchi, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Neural Network Model for Extracting Optic Flow

Kunihiko Fukushima, Kazuya Tohyama, 2005, ICANN.

Recognition of partly occluded patterns: a neural network model

Kunihiko Fukushima, 2001, Biological Cybernetics.

Artificial intelligence and image processing technologies. Biocybernetic approach to pattern recognition.

Kunihiko Fukushima, K. Fukushima, 1987 .

Neural Network Model Completing Occluded Contour

Masayuki Kikuchi, Koichi Anada, Kunihiko Fukushima, 1998, International Conference on Neural Information Processing.

Neocognitron capable of incremental learning

Kunihiko Fukushima, K. Fukushima, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Neocognitron with improved bend-extractors

Hayaru Shouno, Eiji Kimura, Kunihiko Fukushima, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Neocognitron with Non-uniform Receptive Fields

Masato Okada, Kunihiko Fukushima, Kouichirou Yamauchi, 1993 .

Connected character recognition in cursive handwriting using selective attention model with bend processing

Hayaru Shouno, Kunihiko Fukushima, K. Fukushima, 1994, Systems and Computers in Japan.

Analysis of the process of visual pattern recognition by the neocognitron

Kunihiko Fukushima, K. Fukushima, 1989, Neural Networks.

Neural network for connected character recognition

Kunihiko Fukushima, K. Fukushima, 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

Neural network models for vision

Kunihiko Fukushima, K. Fukushima, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Pattern recognition with eye movement: a neural network model

Masayuki Kikuchi, Kunihiko Fukushima, K. Fukushima, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Structure from Stereopsis without Point-to-Point Correspondence

Osamu Watanabe, Kunihiko Fukushima, K. Fukushima, 1997 .

Improved neocognitron with bend-detecting cells

Kunihiko Fukushima, N. Wake, N. Wake, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Artificial vision by multi-layered neural networks: Neocognitron and its advances

Kunihiko Fukushima, K. Fukushima, 2013, Neural Networks.

Neural network model for extracting optic flow

Kunihiko Fukushima, Kazuya Tohyama, K. Fukushima, 2005, Neural Networks.

Neural Network Model Recalling Spatial Maps

Yoshio Yamaguchi, Masato Okada, Kunihiko Fukushima, 1996, ICANN.

Bi-stable concept states in associative memory model

Masato Okada, Kunihiko Fukushima, Kaname Toya, 1997 .

Neocognitron trained by winner-kill-loser with triple threshold

Isao Hayashi, Kunihiko Fukushima, Jasmin Léveillé, 2014, Neurocomputing.

Recognition of spatio-temporal patterns by a multi-layered neural network model

Hiroyuki Miyamoto, Kunihiko Fukushima, K. Fukushima, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

A Computational Model of Stereopsis Using a Stereoscopic Neocognitron

Kunihiko Fukushima, Warren Becraft, K. Fukushima, 1993 .

Self-Organization of Orientation Columns in Area V1 by Synaptic Competition

Kunihiko Fukushima, Hiroyuki Tajima, K. Fukushima, 2001 .

Neural network model restoring partly occluded patterns

Kunihiko Fukushima, 2004 .

Neocognitron: a model for visual pattern recognition

Kunihiko Fukushima, K. Fukushima, 1998 .

Visual Pattern Recognition with Neural Networks

Kunihiko Fukushima, K. Fukushima, 1992, ICPIA.

Selective Motion Analysis Based on Dynamic Visual Saliency Map Model

Minho Lee, Inwon Lee, Kunihiko Fukushima, 2006, ICAISC.

Neocognitron trained by winner-kill-loser with triple threshold

Isao Hayashi, Kunihiko Fukushima, Jasmin Léveillé, 2014, Neurocomputing.

A neural network model for the mechanism of selective attention in visual pattern recognition

Kunihiko Fukushima, 1987, Systems and Computers in Japan.

Neocognitron trained with winner-kill-loser rule

Kunihiko Fukushima, K. Fukushima, 2010, Neural Networks.

Neural network model restoring partly occluded patterns

Kunihiko Fukushima, K. Fukushima, 2003, Int. J. Knowl. Based Intell. Eng. Syst..

Examination of implementing a neural network on a parallel computer — NEOCOGNITRON on NCUBE

Takayuki Ito, Kunihiko Fukushima, Sei Miyake, 1991 .

Improved Learning Method for the Neocognitron

Kunihiko Fukushima, Nobuaki Wake, K. Fukushima, 1992 .

Restoring partly occluded patterns: a neural network model

Kunihiko Fukushima, K. Fukushima, 2005, Neural Networks.

Neural Network for Selective Looking

Kunihiko Fukushima, K. Fukushima, 1994 .

Neocognitron for handwritten digit recognition

Kunihiko Fukushima, K. Fukushima, 2003, Neurocomputing.

Training multi-layered neural network neocognitron

Kunihiko Fukushima, K. Fukushima, 2013, Neural Networks.

Stereo algorithm that extracts a depth cue from interocularly unpaired points

Osamu Watanabe, Kunihiko Fukushima, K. Fukushima, 1999, Neural Networks.

Interpolating Vectors: Powerful Algorithm for Pattern Recognition

Kunihiko Fukushima, K. Fukushima, 2007, ICONIP.

Neocognitron: A neural network model for a mechanism of visual pattern recognition

Takayuki Ito, Kunihiko Fukushima, Sei Miyake, 1983, IEEE Transactions on Systems, Man, and Cybernetics.

A Deep Neural Network Architecture Using Dimensionality Reduction with Sparse Matrices

Petros Boufounos, Manabu Hagiwara, Toshisada Mariyama, 2016, ICONIP.

One-Shot Learning with Feedback for Multi-layered Convolutional Network

Kunihiko Fukushima, 2014, ICANN.

Neural Network Model of the Visual System: Binding Form and Motion

Masayuki Kikuchi, Kunihiko Fukushima, K. Fukushima, 1996, Neural Networks.

Neocognitron learning by backpropagation

Kunihiko Fukushima, Masato Okada, Michihiro Ohno, 1995, Systems and Computers in Japan.

Neural Network Model of Spatial Memory: Associative Recall of Maps

Yoshio Yamaguchi, Masato Okada, Kunihiko Fukushima, 1997, Neural Networks.

Self-Organization of Shift-Invariant Receptive Fields through Pre- and Post-Synaptic Competition

Kunihiko Fukushima, Kazuya Yoshimoto, K. Fukushima, 1998, ICONIP.

Use of different thresholds in learning and recognition

Masashi Tanigawa, Kunihiko Fukushima, K. Fukushima, 1996, Neurocomputing.

A neural network for visual pattern recognition

Kunihiko Fukushima, K. Fukushima, 1988, Computer.

A neural network model for selective attention in visual pattern recognition

Kunihiko Fukushima, K. Fukushima, 1986, Biological Cybernetics.

Restoring Partly Occluded Patterns: A Neural Network Model with Backward Paths

Kunihiko Fukushima, K. Fukushima, 2003, ICANN.

Recognition and segmentation of connected characters with selective attention

Kunihiko Fukushima, Taro Imagawa, K. Fukushima, 1993, Neural Networks.

Neocognitron: A Self-Organizing Neural Network Model for a Mechanism of Visual Pattern Recognition

Kunihiko Fukushima, Sei Miyake, K. Fukushima, 1982 .

Recent Advances in the Neocognitron

Kunihiko Fukushima, K. Fukushima, 2007, ICONIP.

Neural network model of spatial memory

Kunihiko Fukushima, Y. Yamaguchi, K. Fukushima, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Connected character recognition with a neural network

Kunihiko Fukushima, K. Fukushima, 1993, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93).

Modeling Visi 44. Modeling Vision with the Neocognitron

Kunihiko Fukushima, K. Fukushima, 2014 .

Use of top-down signals for restoring partly occluded patterns

Kunihiko Fukushima, K. Fukushima, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Assignment of Figural Side to Contours Based on Symmetry, Parallelism, and Convexity

Masayuki Kikuchi, Kunihiko Fukushima, K. Fukushima, 2003, KES.

A speech recognition system consisting of auditory feature extracting cells and velocity-controlled delay-lines. II. Recognition module

Kunihiko Fukushima, Mitsuhiro Fukuda, Koichiro Yamauchi, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Self-organization of complex-like cells

Kunihiko Fukushima, Kazuya Yoshimoto, K. Fukushima, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

A model of neural network extracting binocular parallax

Yuzo Hirai, Kunihiko Fukushima, 2004, Biological Cybernetics.

Automatic Design of Neural Network Structures Using AiS

Toshisada Mariyama, Wataru Matsumoto, Kunihiko Fukushima, 2016, ICONIP.

Pattern Recognition Research for the Future

Kunihiko Fukushima, K. Fukushima, 1994 .

Margined winner-take-all: New learning rule for pattern recognition

Kunihiko Fukushima, 2018, Neural Networks.

12 – Pattern Recognition with Neural Networks

Kunihiko Fukushima, 1994 .

Response to letter by S. Grossberg

Kunihiko Fukushima, K. Fukushima, 1994, Neural Networks.

A hierarchical neural network model for associative memory

Kunihiko Fukushima, 1983 .

Character recognition in cursive handwriting with the mechanism of selective attention

Kunihiko Fukushima, Taro Imagawa, K. Fukushima, 1993, Systems and Computers in Japan.

Neural Network Capable of Amodal Completion

Kunihiko Fukushima, 2008, ICANN.

Symmetry axis extraction by a neural network

Masayuki Kikuchi, Kunihiko Fukushima, K. Fukushima, 2006, Neurocomputing.

Recognition and segmentation of characters in handwriting with selective attention

Kunihiko Fukushima, Taro Imagawa, K. Fukushima, 1992 .

Online learning of feature detectors from natural images with the probabilistic WKL rule

Isao Hayashi, Kunihiko Fukushima, Jasmin Léveillé, 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

2. Electronics in Image Processing

Kunihiko Fukushima, K. Fukushima, 1972 .

Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Kunihiko Fukushima, K. Fukushima, 1980, Biological Cybernetics.

Self-Organization of Shift-Invariant Receptive Fields

Kunihiko Fukushima, Kazuya Yoshimoto, 1999, IWANN.

Special issue on human mimetics. Modeling visual systems for visual pattern recognition.

Kunihiko Fukushima, K. Fukushima, 1989 .

Self-organizing neural networks with the mechanism of feedback information processing

Kunihiko Fukushima, Sei Miyake, K. Fukushima, 1988 .

Character recognition with selective attention

Kunihiko Fukushima, T. Imagawa, E. Ashida, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.