2008 |
24 | EE | Hamed Akbari,
Yukio Kosugi,
Kazuyuki Kojima,
Naofumi Tanaka:
Wavelet-Based Compression and Segmentation of Hyperspectral Images in Surgery.
MIAR 2008: 142-149 |
2007 |
23 | EE | Sildomar Takahashi Monteiro,
Yukio Kosugi:
A particle swarm optimization-based approach for hyperspectral band selection.
IEEE Congress on Evolutionary Computation 2007: 3335-3340 |
22 | EE | Takashi Hirano,
Shogo Yoneyama,
Yasuhiro Okada,
Yukio Kosugi:
Integrating Vision and Language: Semantic Description of Traffic Events from Image Sequences.
ISVC (2) 2007: 459-468 |
21 | EE | Hamed Akbari,
Yukio Kosugi,
Kazuyuki Kojima,
Toshiaki Ohya,
Hideki Akamatsu,
Naofumi Tanaka:
Enhanced Blood Vessels in Laparoscopy by Using Narrow-Band Imaging.
MVA 2007: 244-247 |
20 | EE | Sildomar Takahashi Monteiro,
Yukio Kosugi:
Particle Swarms for Feature Extraction of Hyperspectral Data.
IEICE Transactions 90-D(7): 1038-1046 (2007) |
2004 |
19 | EE | Iren Valova,
Natacha Gueorguieva,
Yukio Kosugi:
An oscillation-driven neural network for the simulation of an olfactory system.
Neural Computing and Applications 13(1): 65-79 (2004) |
18 | EE | Naoto Mikami,
Yukio Kosugi:
Mutual region growing for adaptive segmentation of geographical images.
Systems and Computers in Japan 35(14): 64-77 (2004) |
2002 |
17 | EE | Noriyuki Take,
Yukio Kosugi,
Toshimitsu Musha:
Three-Dimensional Display for Multi-sourced Activities and Their Relations in the Human Brain by Information Flow between Estimated Dipoles.
MICCAI (2) 2002: 93-100 |
16 | EE | Keisuke Kameyama,
Kazuo Toraichi,
Yukio Kosugi:
Constructive Relaxation Matching Involving Dynamical Model Switching and Its Application to Shape Matching.
Int. J. Image Graphics 2(4): 655-668 (2002) |
2001 |
15 | EE | Hiroyuki Aoki,
Eiju Watanabe,
Atsushi Nagata,
Yukio Kosugi:
Rotation-Invariant Image Association for Endoscopic Positional Identification Using Complex-Valued Associative Memories.
IWANN (2) 2001: 369-376 |
2000 |
14 | EE | Hiroyuki Aoki,
Yukio Kosugi:
An Image Storage System Using Complex-Valued Associative Memories.
ICPR 2000: 2626-2629 |
13 | | Iren Valova,
Yukio Kosugi:
Hadamard-based image decomposition and compression.
IEEE Transactions on Information Technology in Biomedicine 4(4): 306-319 (2000) |
1999 |
12 | | Kazuhiro Matsui,
Yukio Kosugi:
Image Segmentation by Neural-Net Classifiers with Genetic Selection of Feature Indices.
ICIP (1) 1999: 524-528 |
11 | EE | Manabu Motegi,
Yukio Kosugi:
Self-organizing elastic networks for generating a 3D model for many images.
Systems and Computers in Japan 30(12): 106-115 (1999) |
10 | EE | Kazuhiro Matsui,
Yusuke Suganami,
Yukio Kosugi:
Feature selection by genetic algorithm for MRI segmentation.
Systems and Computers in Japan 30(7): 69-78 (1999) |
9 | EE | Naoko Uemoto,
Yukio Kosugi:
Dynamic regularization for the restoration of PET images.
Systems and Computers in Japan 30(8): 23-31 (1999) |
1998 |
8 | | Takehiko Ogawa,
Yukio Kosugi,
Hajime Kanada:
Bispectrum Estimation by Recurrent Network with Third-Order Moment Controllable Noise Source.
ICONIP 1998: 1145-1148 |
7 | | Kazuhiro Matsui,
Yukio Kosugi:
Image Segmentation Using Genetic Method to Select Feature Indices.
ICONIP 1998: 352-355 |
6 | | Kuniaki Uto,
Yukio Kosugi:
Segmented Representation of Approximation Surface.
ICONIP 1998: 75-78 |
5 | EE | Kuniaki Uto,
Yukio Kosugi:
Ill-posed problems arising in image-guided navigation systems and a network realization based on spline interpolation.
Systems and Computers in Japan 29(10): 36-45 (1998) |
4 | EE | Takehiko Ogawa,
Yukio Kosugi:
A neural network for identification of economic indicators using an answer-in-weights scheme.
Systems and Computers in Japan 29(5): 29-36 (1998) |
1994 |
3 | | Mikiya Sase,
Naoyuki Kinoshita,
Yukio Kosugi:
A Neural Network for Fusing the MR Information into PET Images to Improve Spatial Resolution.
ICIP (3) 1994: 908-911 |
2 | EE | Jun Takeuchi,
Yukio Kosugi:
Neural network representation of finite element method.
Neural Networks 7(2): 389-395 (1994) |
1992 |
1 | EE | Jun Ogata,
Mikiya Sase,
Yukio Kosugi:
Neural Network Approaches for Attractive Area Extraction from Video Images.
MVA 1992: 159-162 |