Haruhisa Takahashi

According to our database1, Haruhisa Takahashi authored at least 35 papers between 1986 and 2015.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


Estimation of Average Latent Waiting and Service Times of Activities from Event Logs.
Proceedings of the Business Process Management - 13th International Conference, 2015

Learning with Kernel Random Field and Linear SVM.
Proceedings of the ICPRAM 2014, 2014

Improving object position estimation based on non-linear mapping using Relevance Vector Machine.
Proceedings of the CONIELECOMP 2011, 21st International Conference on Electrical, Communications, and Computers, 28 February, 2011

Asbestos Detection in Building Materials Through Consolidation of Similarities in Color and Shape Features.
JRM, 2010

Development of an Automated Microscope for Supporting Qualitative Asbestos Analysis by Dispersion Staining.
JRM, 2009

Implementation Issues of Second-Order Cone Programming Approaches for Support Vector Machine Learning Problems.
IEICE Transactions, 2009

Improving the eigenphase method for face recognition.
IEICE Electronic Express, 2009

Action Recognition Based on Non-parametric Probability Density Function Estimation.
Proceedings of the Advances in Visual Computing, 5th International Symposium, 2009

Estimation of Object Position Based on Color and Shape Contextual Information.
Proceedings of the Image Analysis and Processing, 2009

Face Recognition Based on Normalization and the Phase Spectrum of the Local Part of an Image.
Proceedings of the Advances in Visual Computing, 4th International Symposium, 2008

An Asbestos Counting Method from Microscope Images of Building Materials Using Summation Kernel of Color and Shape.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Asbestos Detection from Microscope Images Using Support Vector Random Field of Local Color Features.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Automatic Particle Detection and Counting by One-Class SVM from Microscope Image.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Variational phasor mean field model for Markov random fields.
Proceedings of the 9th International Symposium on Signal Processing and Its Applications, 2007

The worst-case time complexity for generating all maximal cliques and computational experiments.
Theor. Comput. Sci., 2006

An Object Detection Method Based on Independent Local Features.
JRM, 2006

SVM Training: Second-Order Cone Programming versus Quadratic Programming.
Proceedings of the International Joint Conference on Neural Networks, 2006

An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems.
Appl. Intell., 2005

The Variational Correlation Network for Object Detection.
Proceedings of the 2005 International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA 2005), 2005

A decision based one-against-one method for multi-class support vector machine.
Pattern Anal. Appl., 2004

Kernel Selection for the Support Vector Machine.
IEICE Transactions, 2004

Lipreading Using Recurrent Neural Prediction Model.
Proceedings of the Image Analysis and Recognition: International Conference, 2004

A New Model for Large Margin Classifiers by Second Order Cone Programming.
Proceedings of the International Conference on Artificial Intelligence, 2004

The Worst-Case Time Complexity for Generating All Maximal Cliques.
Proceedings of the Computing and Combinatorics, 10th Annual International Conference, 2004

Speech recognition using recurrent neural prediction model.
Systems and Computers in Japan, 2003

A Fast Learning Decision-Based SVM for Multi-Class Problems.
Proceedings of the 2003 International Conference on Machine Learning and Applications, 2003

Learning Capability: Classical RBF Network vs. SVM with Gaussian Kernel.
Proceedings of the Developments in Applied Artificial Intelligence, 2002

How Bad May Learning Curves Be?.
IEEE Trans. Pattern Anal. Mach. Intell., 2000

Exponential or Polynomial Learning Curves? Case-Based Studies.
Neural Computation, 2000

A tight bound on concept learning.
IEEE Trans. Neural Networks, 1998

Estimating Learning Curves of Concept Learning.
Neural Networks, 1997

Towards more practical average bounds on supervised learning.
IEEE Trans. Neural Networks, 1996

A randomized algorithm for finding a near-maximum clique and its experimental evaluations.
Systems and Computers in Japan, 1994

Separability of internal representations in multilayer perceptrons with application to learning.
Neural Networks, 1993

Mean and Variance of Overflow Traffic for Time Dependent Inputs.
IEEE Trans. Communications, 1986