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Haruhisa Takahashi
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2010 – 2019
- 2015
- [c17]Takahide Nogayama, Haruhisa Takahashi:
Estimation of Average Latent Waiting and Service Times of Activities from Event Logs. BPM 2015: 172-179 - 2014
- [c16]Haruhisa Takahashi:
Learning with Kernel Random Field and Linear SVM. ICPRAM 2014: 167-174 - 2011
- [c15]Jesus Robles-Castro, Gonzalo Duchen-Sanchez
, Haruhisa Takahashi:
Improving object position estimation based on non-linear mapping using Relevance Vector Machine. CONIELECOMP 2011: 171-176 - 2010
- [j20]Atsuo Nomoto, Kazuhiro Hotta, Haruhisa Takahashi:
Asbestos Detection in Building Materials Through Consolidation of Similarities in Color and Shape Features. J. Robotics Mechatronics 22(4): 496-505 (2010)
2000 – 2009
- 2009
- [j19]Jesus Olivares-Mercado
Improving the eigenphase method for face recognition. IEICE Electron. Express 6(15): 1112-1117 (2009) - [j18]Rameswar Debnath
Implementation Issues of Second-Order Cone Programming Approaches for Support Vector Machine Learning Problems. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 92-A(4): 1209-1222 (2009) - [j17]Kuniaki Kawabata
Development of an Automated Microscope for Supporting Qualitative Asbestos Analysis by Dispersion Staining. J. Robotics Mechatronics 21(2): 186-192 (2009) - [c14]Takashi Ishihara, Kazuhiro Hotta, Haruhisa Takahashi:
Estimation of Object Position Based on Color and Shape Contextual Information. ICIAP 2009: 825-834 - [c13]Yuta Mimura, Kazuhiro Hotta, Haruhisa Takahashi:
Action Recognition Based on Non-parametric Probability Density Function Estimation. ISVC (2) 2009: 489-498 - 2008
- [c12]Yoshitaka Moriguchi, Kazuhiro Hotta, Haruhisa Takahashi:
Asbestos Detection from Microscope Images Using Support Vector Random Field of Local Color Features. ICONIP (2) 2008: 344-352 - [c11]Hinata Kuba, Kazuhiro Hotta, Haruhisa Takahashi:
Automatic Particle Detection and Counting by One-Class SVM from Microscope Image. ICONIP (2) 2008: 361-368 - [c10]Atsuo Nomoto, Kazuhiro Hotta, Haruhisa Takahashi:
An Asbestos Counting Method from Microscope Images of Building Materials Using Summation Kernel of Color and Shape. ICONIP (2) 2008: 671-678 - [c9]Jesus Olivares-Mercado
Face Recognition Based on Normalization and the Phase Spectrum of the Local Part of an Image. ISVC (2) 2008: 278-286 - 2007
- [c8]Haruhisa Takahashi:
Variational phasor mean field model for Markov random fields. ISSPA 2007: 1-4 - 2006
- [j16]Ryouta Nakano, Kazuhiro Hotta, Haruhisa Takahashi:
An Object Detection Method Based on Independent Local Features. J. Robotics Mechatronics 18(6): 744-750 (2006) - [j15]Etsuji Tomita, Akira Tanaka, Haruhisa Takahashi:
The worst-case time complexity for generating all maximal cliques and computational experiments. Theor. Comput. Sci. 363(1): 28-42 (2006) - [c7]Rameswar Debnath
SVM Training: Second-Order Cone Programming versus Quadratic Programming. IJCNN 2006: 1162-1168 - 2005
- [j14]Rameswar Debnath
An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems. Appl. Intell. 23(3): 219-239 (2005) - [c6]Haruhisa Takahashi:
The Variational Correlation Network for Object Detection. CIMCA/IAWTIC 2005: 314-320 - 2004
- [j13]Rameswar Debnath, Haruhisa Takahashi:
Kernel Selection for the Support Vector Machine. IEICE Trans. Inf. Syst. 87-D(12): 2903-2904 (2004) - [j12]Rameswar Debnath
A decision based one-against-one method for multi-class support vector machine. Pattern Anal. Appl. 7(2): 164-175 (2004) - [c5]Etsuji Tomita, Akira Tanaka, Haruhisa Takahashi:
The Worst-Case Time Complexity for Generating All Maximal Cliques. COCOON 2004: 161-170 - [c4]Rameswar Debnath, Masakazu Muramatsu, Haruhisa Takahashi:
A New Model for Large Margin Classifiers by Second Order Cone Programming. IC-AI 2004: 877-882 - [c3]Takuya Tsunekawa, Kazuhiro Hotta, Haruhisa Takahashi:
Lipreading Using Recurrent Neural Prediction Model. ICIAR (2) 2004: 405-412 - 2003
- [j11]Toru Uchiyama, Haruhisa Takahashi:
Speech recognition using recurrent neural prediction model. Syst. Comput. Jpn. 34(2): 100-107 (2003) - [c2]Rameswar Debnath, N. Takahide, Haruhisa Takahashi:
A Fast Learning Decision-Based SVM for Multi-Class Problems. ICMLA 2003: 128-134 - 2002
- [c1]Rameswar Debnath, Haruhisa Takahashi:
Learning Capability: Classical RBF Network vs. SVM with Gaussian Kernel. IEA/AIE 2002: 293-302 - 2000
- [j10]Hanzhong Gu, Haruhisa Takahashi:
Exponential or Polynomial Learning Curves? Case-Based Studies. Neural Comput. 12(4): 795-809 (2000) - [j9]Hanzhong Gu, Haruhisa Takahashi:
How Bad May Learning Curves Be?. IEEE Trans. Pattern Anal. Mach. Intell. 22(10): 1155-1167 (2000)
1990 – 1999
- 1998
- [j8]Haruhisa Takahashi, Hanzhong Gu:
A tight bound on concept learning. IEEE Trans. Neural Networks 9(6): 1191-1202 (1998) - 1997
- [j7]Hanzhong Gu, Haruhisa Takahashi:
Estimating Learning Curves of Concept Learning. Neural Networks 10(6): 1089-1102 (1997) - 1996
- [j6]Hanzhong Gu, Haruhisa Takahashi:
Towards more practical average bounds on supervised learning. IEEE Trans. Neural Networks 7(4): 953-968 (1996) - 1994
- [j5]Yoshiaki Yamada, Etsuji Tomita, Haruhisa Takahashi:
A randomized algorithm for finding a near-maximum clique and its experimental evaluations. Syst. Comput. Jpn. 25(2): 1-7 (1994) - 1993
- [j4]Haruhisa Takahashi, Etsuji Tomita, Tsutomu Kawabata:
Separability of internal representations in multilayer perceptrons with application to learning. Neural Networks 6(5): 689-703 (1993)
1980 – 1989
- 1986
- [j3]Haruo Akimaru, Atsushi Kagechika, Haruhisa Takahashi:
Mean and Variance of Overflow Traffic for Time Dependent Inputs. IEEE Trans. Commun. 34(3): 238-243 (1986) - 1983
- [j2]Haruo Akimaru, Haruhisa Takahashi:
An Approximate Formula for Individual Call Losses in Overflow Systems. IEEE Trans. Commun. 31(6): 808-811 (1983) - 1981
- [j1]Haruo Akimaru, Haruhisa Takahashi:
Asymptotic Expansion for Erlang Loss Function and Its Derivative. IEEE Trans. Commun. 29(9): 1257-1260 (1981)
Coauthor Index
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