K. Kameyama

发表

Image Resolution Conversion Based on an Edge-Adaptive Interpolation Kernel

K. Toraichi, K. Kameyama, K. Toraichi, 2007, 2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing.

An algorithm for model determination in a layered network with non-uniform hidden layer unit set

Y. Kosugi, K. Kameyama, 2002 .

Texture Classification by Adaptive Extraction of Second and Third-Order Statistical Features

Y. Kosugi, K. Kameyama, K. Mori, 2002 .

Extraction of Hyperspectral Data for under Spilled Blood Visualization Using Particle Swarm Optimization

E. Watanabe, Y. Kosugi, S. Monteiro, 2005 .

Feature Extraction of Hyperspectral Data for under Spilled Blood Visualization Using Particle Swarm Optimization

Keisuke Kameyama, Yukio Kosugi, Sildomar T. Monteiro, 2005 .

CONTENT-BASED RETRIEVAL OF KAMON IMAGES BY IMAGE SMOOTHING AND RELAXATION

N. Otsu, T. Kurita, K. Toraichi, 2004 .

Neural network pruning by fusing hidden layer units

Keisuke Kameyama, Yukio Kosugi, Y. Kosugi, 1991 .

Image Matching based on Relaxation and Model Switching on Contour Characterization

Y. Kosugi, K. Toraichi, K. Kameyama, 2002 .

Neural Network Model Switching for Efficient Feature Extraction

Keisuke Kameyama, Yukio Kosugi, Y. Kosugi, 1999 .

Source Localization with Network Inversion Using an Answer-in-Weights Scheme

Keisuke Kameyama, Yukio Kosugi, Roman Kuc, 1996 .

A comparative study using contours and skeletons as shape representations for binary image matching

Keisuke Kameyama, Houssem Chatbri, Paul Wing Hing Kwan, 2016, Pattern Recognit. Lett..

On a relaxation-labeling algorithm for real-time contour-based image similarity retrieval

Keisuke Kameyama, Kazuo Toraichi, Paul Wing Hing Kwan, 2003, Image Vis. Comput..

Particle Swarm Optimization - A Survey

Keisuke Kameyama, K. Kameyama, 2009, IEICE Trans. Inf. Syst..

Informative Band Subset Selection for Hyperspectral Image Classification using Joint and Conditional Mutual Information

K. Kameyama, U. Ali, 2022, 2022 IEEE Symposium Series on Computational Intelligence (SSCI).

Relevance tuning in content-based retrieval of structurally-modeled images using Particle Swarm Optimization

Keisuke Kameyama, Nozomi Oka, K. Kameyama, 2009, 2009 IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing.

Optimization of Similarity Evaluation Algorithm Using Relevance Feedback in Content-Based Image Retrieval

Keisuke Kameyama, Kazuo Toraichi, Nozomi Oka, 2007 .

Relevance Optimization in Image Database Using Feature Space Preference Mapping and Particle Swarm Optimization

Keisuke Kameyama, Nozomi Oka, Mayuko Okayama, 2007, ICONIP.

Content-Based Image Retrieval of Kaou Images by Relaxation Matching of Region Features

Keisuke Kameyama, Takashi Yamamoto, Soo-Nyoun Kim, 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

TAST-Trademark Application Assistant

Keisuke Kameyama, Kazuo Toraichi, Paul Wing Hing Kwan, 2002, Proceedings. International Conference on Image Processing.

Partial image retrieval using SIFT based on illumination invariant features

Keisuke Kameyama, K. Kameyama, Masaki Kobayashi, 2010, 2010 International Conference on Multimedia Computing and Information Technology (MCIT).

Multi-Stage Model Compression using Teacher Assistant and Distillation with Hint-Based Training

K. Kameyama, Takumi Morikawa, 2022, 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).

An Image Segmentation Method for Function Approximation of Gradation Images

Keisuke Kameyama, Tetsuo Kamina, Kazuo Toraichi, 2006, SPPRA.

Connecting image similarity retrieval with consistent labeling problem by introducing a match-all label

Keisuke Kameyama, Kazuo Toraichi, Paul Wing Hing Kwan, 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

A Function Approximation Method for Images with Grading Regions

Keisuke Kameyama, Tetsuo Kamina, Kazuo Toraichi, 2009, Int. J. Image Graph..

Document image dataset indexing and compression using connected components clustering

Keisuke Kameyama, Houssem Chatbri, K. Kameyama, 2015, 2015 14th IAPR International Conference on Machine Vision Applications (MVA).

A novel shape descriptor based on salient keypoints detection for binary image matching and retrieval

P. Kwan, K. Kameyama, S. Little, 2018, Multimedia tools and applications.

Shape matching using keypoints extracted from both the foreground and the background of binary images

Keisuke Kameyama, Houssem Chatbri, Kenny Davila, 2015, 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA).

Towards a segmentation and recognition-free approach for content-based document image retrieval of handwritten queries

Keisuke Kameyama, Houssem Chatbri, Paul Kwan, 2015, 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR).

Sketch-Based Image Retrieval by Size-Adaptive and Noise-Robust Feature Description

Keisuke Kameyama, Houssem Chatbri, Paul Wing Hing Kwan, 2013, 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

INVITED PAPER Special Section on Large Scale Algorithms for Learning and Optimization Particle Swarm Optimization - A Survey

Keisuke Kameyama, K. Kameyama, 2009 .

Composite Color Invariant Feature H′ Applied to Image Matching

Keisuke Kameyama, Wataru Matsumoto, K. Kameyama, 2013, ICONIP.

Joint use of luminance and color invariants in partial image retrieval

K. Kameyama, Wataru Matsumoto, 2013, 2013 International Symposium on Intelligent Signal Processing and Communication Systems.

A Composite Illumination Invariant Color Feature and Its Application to Partial Image Matching

Keisuke Kameyama, Masaki Kobayashi, K. Kameyama, 2012, IEICE Trans. Inf. Syst..

Machine Learning Curriculums Generated by Classifier Ensembles

K. Kameyama, Tzu-Jui Huang, 2023, International Colloquium on Signal Processing and Its Applications.

An Application-Independent and Segmentation-Free Approach for Spotting Queries in Document Images

Keisuke Kameyama, Houssem Chatbri, Paul Wing Hing Kwan, 2014, 2014 22nd International Conference on Pattern Recognition.

Using scale space filtering to make thinning algorithms robust against noise in sketch images

Keisuke Kameyama, Houssem Chatbri, K. Kameyama, 2014, Pattern Recognit. Lett..

Active Learning with Interpretable Predictor

Hideitsu Hino, Keisuke Kameyama, Yusuke Taguchi, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

A modular approach for query spotting in document images and its optimization using genetic algorithms

Keisuke Kameyama, Houssem Chatbri, Paul Wing Hing Kwan, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

A Shape-Directed Scaling Method for Fundus Image with Maintenance to Blood-Vessel Shapes and Color Reality

Keisuke Kameyama, Kazuo Toraichi, Yasuhiro Ohmiya, 2005 .

CNN Model Compression by Merit-Based Distillation

K. Kameyama, Takumi Morikawa, 2023, 2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA).

Parameter Density Inheritance Using Kernel Density Estimation for Efficient CNN Learning

Keisuke Kameyama, Keisuke Horiuchi, K. Kameyama, 2018, 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).