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2020 – today
- 2020
[j44]Jonathan Mojoo, Yu Zhao, Muthu Subash Kavitha, Jun'ichi Miyao, Takio Kurita:
Completion of Missing Labels for Multi-Label Annotation by a Unified Graph Laplacian Regularization. IEICE Trans. Inf. Syst. 103-D(10): 2154-2161 (2020)- [j43]Hidenori Ide, Takumi Kobayashi, Kenji Watanabe, Takio Kurita
:
Robust pruning for efficient CNNs. Pattern Recognit. Lett. 135: 90-98 (2020) - [j42]Novanto Yudistira, Takio Kurita:
Correlation Net: Spatiotemporal multimodal deep learning for action recognition. Signal Process. Image Commun. 82: 115731 (2020) - [c118]Xiaohan Wang, Jun'ichi Miyao, Takio Kurita:
Short-Term Action Recognition by 3D Convolutional Neural Network with Pixel-Wise Evidences. IW-FCV 2020: 69-82 - [c117]Keijiro Kanda, Muthu Subash Kavitha, Jun'ichi Miyao, Takio Kurita:
Analysis of Information Flow in Hidden Layers of the Trained Neural Network by Canonical Correlation Analysis. IW-FCV 2020: 206-220 - [c116]Shah B. Shrey, Lukman Hakim, Muthu Subash Kavitha, Hae Won Kim, Takio Kurita:
Transfer Learning by Cascaded Network to Identify and Classify Lung Nodules for Cancer Detection. IW-FCV 2020: 262-273 - [c115]Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
Adaptive Neuron-wise Discriminant Criterion and Adaptive Center Loss at Hidden Layer for Deep Convolutional Neural Network. IJCNN 2020: 1-8 - [c114]Kakeru Mitsuno, Jun'ichi Miyao, Takio Kurita:
Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks. IJCNN 2020: 1-8 - [c113]Hideki Oki, Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
Triplet Loss for Knowledge Distillation. IJCNN 2020: 1-7 - [c112]Ueda Ueda, Yuichiro Nomura, Jun'ichi Miyao, Takio Kurita, Hiroshi Yamada:
Non-negative Matrix Factorization of a set of Economic Time Series with Graph Based Smoothing of Basis Vectors and Sparseness of the Coefficients. SMC 2020: 824-829 - [i15]Fangda Zhao, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda:
On-line non-overlapping camera calibration net. CoRR abs/2002.08005 (2020) - [i14]Kakeru Mitsuno, Jun'ichi Miyao, Takio Kurita:
Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks. CoRR abs/2004.04394 (2020) - [i13]Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
Adaptive Neuron-wise Discriminant Criterion and Adaptive Center Loss at Hidden Layer for Deep Convolutional Neural Network. CoRR abs/2004.08074 (2020) - [i12]Hideki Oki, Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
Triplet Loss for Knowledge Distillation. CoRR abs/2004.08116 (2020) - [i11]Lukman Hakim, Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita:
U-Net with Graph Based Smoothing Regularizer for Small Vessel Segmentation on Fundus Image. CoRR abs/2009.07567 (2020) - [i10]Shah B. Shrey, Lukman Hakim, Muthu Subash Kavitha, Hae Won Kim, Takio Kurita:
Transfer Learning by Cascaded Network to identify and classify lung nodules for cancer detection. CoRR abs/2009.11587 (2020) - [i9]Kakeru Mitsuno, Takio Kurita:
Filter Pruning using Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks. CoRR abs/2011.02389 (2020) - [i8]Kakeru Mitsuno, Yuichiro Nomura, Takio Kurita:
Channel Planting for Deep Neural Networks using Knowledge Distillation. CoRR abs/2011.02390 (2020) - [i7]Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
q-SNE: Visualizing Data using q-Gaussian Distributed Stochastic Neighbor Embedding. CoRR abs/2012.00999 (2020) - [i6]Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita:
Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN. CoRR abs/2012.09542 (2020)
2010 – 2019
- 2019
- [j41]Rarasmaya Indraswari, Takio Kurita, Agus Zainal Arifin, Nanik Suciati, Eha Renwi Astuti:
Multi-projection deep learning network for segmentation of 3D medical images. Pattern Recognit. Lett. 125: 791-797 (2019) - [j40]Novanto Yudistira, Takio Kurita:
Deep Packet Flow: Action Recognition via Multiresolution Deep Wavelet Packet of Local Dense Optical Flows. J. Signal Process. Syst. 91(6): 609-625 (2019) - [c111]Muthu Subash Kavitha, Novanto Yudistira, Takio Kurita:
Multi instance learning via deep CNN for multi-class recognition of Alzheimer's disease. IWCIA 2019: 89-94 - [c110]Qien Yu, Muthu Subash Kavitha, Takio Kurita:
Detection of One Dimensional Anomalies Using a Vector-Based Convolutional Autoencoder. ACPR (2) 2019: 516-529 - [c109]Nasrulloh R. B. S. Loka, Muthu Subash Kavitha, Takio Kurita:
Hilbert Vector Convolutional Neural Network: 2D Neural Network on 1D Data. ICANN (1) 2019: 458-470 - [c108]Jonathan Mojoo, Yu Zhao, Muthu Subash Kavitha, Jun'ichi Miyao, Takio Kurita:
Learning with Incomplete Labels for Multi-label Image Annotation Using CNN and Restricted Boltzmann Machines. ICONIP (2) 2019: 286-298 - [c107]Hideki Oki, Jun'ichi Miyao, Takio Kurita:
Siamese Network for Classification with Optimization of AUC. ICONIP (2) 2019: 315-327 - [c106]Lukman Hakim, Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita:
U-Net with Graph Based Smoothing Regularizer for Small Vessel Segmentation on Fundus Image. ICONIP (5) 2019: 515-522 - [c105]Jonathan Mojoo, Motaz Sabri, Takio Kurita:
Video Super Resolution with Estimation of Motion Information by Using Higher Resolution Images Obtained by Single Image Super Resolution. IJCNN 2019: 1-8 - [i5]Hideki Oki, Takio Kurita:
Mixup of Feature Maps in a Hidden Layer for Training of Convolutional Neural Network. CoRR abs/1906.09739 (2019) - 2018
- [j39]Muthu Subash Kavitha, Takio Kurita, Byeong-Cheol Ahn:
Critical texture pattern feature assessment for characterizing colonies of induced pluripotent stem cells through machine learning techniques. Comput. Biol. Medicine 94: 55-64 (2018) - [j38]Motaz Sabri, Takio Kurita:
Facial expression intensity estimation using Siamese and triplet networks. Neurocomputing 313: 143-154 (2018) - [j37]Fangda Zhao, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda:
Marker-based non-overlapping camera calibration methods with additional support camera views. Image Vis. Comput. 70: 46-54 (2018) - [j36]Shohei Kumagai, Kazuhiro Hotta, Takio Kurita:
Mixture of counting CNNs. Mach. Vis. Appl. 29(7): 1119-1126 (2018) - [c104]Hidenori Ide, Takio Kurita:
Convolutional Neural Network with Discriminant Criterion for Input of Each Neuron in Output Layer. ICONIP (1) 2018: 332-339 - [c103]Hideki Oki, Takio Kurita:
Mixup of Feature Maps in a Hidden Layer for Training of Convolutional Neural Network. ICONIP (2) 2018: 635-644 - [c102]Ryusuke Yamada, Hidenori Ide, Novanto Yudistira, Takio Kurita:
Texture Segmentation using Siamese Network and Hierarchical Region Merging. ICPR 2018: 2735-2740 - [c101]Rarasmaya Indraswari, Takio Kurita, Agus Zainal Arifin, Nanik Suciati, Eha Renwi Astuti, Dini Adni Navastara:
3D Region Merging for Segmentation of Teeth on Cone-Beam Computed Tomography Images. SCIS&ISIS 2018: 341-345 - [i4]Novanto Yudistira, Takio Kurita:
Correlation Net : spatio temporal multimodal deep learning. CoRR abs/1807.08291 (2018) - 2017
- [j35]Tsubasa Hirakawa, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda, Chaohui Wang, Laurent Najman:
Tree-Wise Discriminative Subtree Selection for Texture Image Labeling. IEEE Access 5: 13617-13634 (2017) - [j34]Novanto Yudistira, Takio Kurita:
Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning. EURASIP J. Image Video Process. 2017: 85 (2017) - [j33]Motaz Sabri, Takio Kurita:
Effect of Additive Noise for Multi-Layered Perceptron with AutoEncoders. IEICE Trans. Inf. Syst. 100-D(7): 1494-1504 (2017) - [c100]Novanto Yudistira, Takio Kurita:
Temporal Evolution of Motion Superpixel for Video Classification. CYBCONF 2017: 1-6 - [c99]Jonathan Mojoo, Keiichi Kurosawa, Takio Kurita:
Deep CNN with Graph Laplacian Regularization for Multi-label Image Annotation. ICIAR 2017: 19-26 - [c98]Jin Yamanaka, Shigesumi Kuwashima, Takio Kurita:
Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network. ICONIP (2) 2017: 217-225 - [c97]Hiromu Fujishige, Jun'ichi Miyao, Takio Kurita:
Image Inpainting by Recursive Estimation Using Neural Network and Wavelet Transformation. ICONIP (6) 2017: 652-661 - [c96]Hidenori Ide, Takio Kurita:
Improvement of learning for CNN with ReLU activation by sparse regularization. IJCNN 2017: 2684-2691 - [i3]Shohei Kumagai, Kazuhiro Hotta, Takio Kurita:
Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting. CoRR abs/1703.09393 (2017) - [i2]Jin Yamanaka, Shigesumi Kuwashima, Takio Kurita:
Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network. CoRR abs/1707.05425 (2017) - 2016
- [j32]Akinori Hidaka, Takio Kurita:
Optimum Nonlinear Discriminant Analysis and Discriminant Kernel Support Vector Machine. IEICE Trans. Inf. Syst. 99-D(11): 2734-2744 (2016) - [c95]Tsubasa Hirakawa, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda, Chaohui Wang, Laurent Najman, Tetsushi Koide, Shigeto Yoshida, Hiroshi Mieno, Shinji Tanaka:
Discriminative Subtree Selection for NBI Endoscopic Image Labeling. ACCV Workshops (2) 2016: 610-624 - [c94]Fangda Zhao, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda:
Marker based simple non-overlapping camera calibration. ICIP 2016: 1180-1184 - [c93]Hidenori Ide, Takio Kurita:
Low level visual feature extraction by learning of multiple tasks for Convolutional Neural Networks. IJCNN 2016: 3620-3627 - [c92]Bisser Raytchev, Atsuki Masuda, Masatoshi Minakawa, Kojiro Tanaka, Takio Kurita, Toru Imamura, Masashi Suzuki, Toru Tamaki, Kazufumi Kaneda:
Detection of Differentiated vs. Undifferentiated Colonies of iPS Cells Using Random Forests Modeled with the Multivariate Polya Distribution. MICCAI (2) 2016: 667-675 - [i1]Toru Tamaki, Shoji Sonoyama, Takio Kurita, Tsubasa Hirakawa, Bisser Raytchev, Kazufumi Kaneda, Tetsushi Koide, Shigeto Yoshida, Hiroshi Mieno, Shinji Tanaka, Kazuaki Chayama:
Domain Adaptation with L2 constraints for classifying images from different endoscope systems. CoRR abs/1611.02443 (2016) - 2015
- [j31]Takashi Takahashi, Takio Kurita:
Mixture of Subspaces Image Representation and Compact Coding for Large-Scale Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 37(7): 1469-1479 (2015) - [c91]Shoji Sonoyama, Tsubasa Hirakawa, Toru Tamaki, Takio Kurita, Bisser Raytchev, Kazufumi Kaneda, Tetsushi Koide, Shigeto Yoshida, Yoko Kominami, Shinji Tanaka:
Transfer learning for Bag-of-Visual words approach to NBI endoscopic image classification. EMBC 2015: 785-788 - [c90]Xuezhen Li, Takio Kurita:
Nonlinear discriminant analysis using K nearest neighbor estimation. FCV 2015: 1-6 - [c89]Atsuki Masuda, Bisser Raytchev, Takio Kurita, Toru Imamura, Masashi Suzuki, Toru Tamaki, Kazufumi Kaneda:
Automatic Detection of Good/Bad Colonies of iPS Cells Using Local Features. MLMI 2015: 153-160 - [c88]Novanto Yudistira, Takio Kurita:
Multiresolution Local Autocorrelation of Optical Flows over Time for Action Recognition. SMC 2015: 1930-1935 - [c87]Ran Li, Xuezhen Li, Takio Kurita:
Soft local binary patterns. SoCPaR 2015: 70-75 - 2014
- [j30]Zhouxin Yang, Takio Kurita:
Improvements of Local Descriptor in HOG/SIFT by BOF Approach. IEICE Trans. Inf. Syst. 97-D(5): 1293-1303 (2014) - [j29]Takashi Takahashi, Takio Kurita:
Image Classification Using a Mixture of Subspace Models. IPSJ Trans. Comput. Vis. Appl. 6: 93-97 (2014) - [c86]Takio Kurita, Yayoi Harashima:
Extraction of Dimension Reduced Features from Empirical Kernel Vector. ICONIP (2) 2014: 9-16 - [c85]Akinori Hidaka, Takio Kurita:
Nonlinear Discriminant Analysis Based on Probability Estimation by Gaussian Mixture Model. S+SSPR 2014: 133-142 - [r1]Takio Kurita:
Principal Component Analysis (PCA). Computer Vision, A Reference Guide 2014: 636-639 - 2013
- [c84]Zhouxin Yang, Takio Kurita:
Improvements to the Descriptor of SIFT by BOF Approaches. ACPR 2013: 95-99 - [c83]Zhibin Zhang, Xuezhen Li, Takio Kurita, Shinya Tanaka:
Pixel-Pair Features Selection for Vehicle Tracking. ACPR 2013: 471-475 - [c82]Xiaoying Guo, Takio Kurita, Chie Muraki Asano, Akira Asano:
Visual complexity assessment of painting images. ICIP 2013: 388-392 - [c81]Zhouxin Yang, Takio Kurita:
BOG: An extension of HOG by interpreting it as bag of features. MVA 2013: 415-418 - [c80]Takio Kurita, Kenji Watanabe, Akinori Hidaka:
Sparse Logistic Discriminant Analysis. SMC 2013: 3003-3008 - 2012
- [j28]Muthu Subash Kavitha, Akira Asano, Akira Taguchi, Takio Kurita, Mitsuhiro Sanada:
Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system. BMC Medical Imaging 12: 1 (2012) - [j27]Lei Yang, Akira Asano, Liang Li, Chie Muraki Asano, Takio Kurita:
Multi-Structural Texture Analysis Using Mathematical Morphology. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 95-A(10): 1759-1767 (2012) - [j26]Tetsu Matsukawa, Takio Kurita:
Image representation for generic object recognition using higher-order local autocorrelation features on posterior probability images. Pattern Recognit. 45(2): 707-719 (2012) - [c79]Takahishi Takeda, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Takio Kurita, Shigeto Yoshida, Yoshito Takemura, Keiichi Onji, Rie Miyaki, Shinji Tanaka:
Self-training with unlabeled regions for NBI image recognition. ICPR 2012: 25-28 - [c78]Muthu Subash Kavitha, Takio Kurita, Akira Asano, Akira Taguchi:
Automatic assessment of mandibular bone using support vector machine for the diagnosis of osteoporosis. SMC 2012: 214-219 - [c77]Akinori Hidaka, Takio Kurita:
Sparse Discriminant Analysis Based on the Bayesian Posterior Probability Obtained by L1 Regression. SSPR/SPR 2012: 648-656 - 2011
- [c76]Tetsu Matsukawa, Takio Kurita:
Discriminant appearance weighting for action recognition. ACPR 2011: 7-11 - [c75]Akinori Hidaka, Takio Kurita:
Discriminant kernels based support vector machine. ACPR 2011: 159-163 - [c74]Kenji Nishida, Jun Fujiki, Takio Kurita:
Multiple Random Subset-Kernel Learning. CAIP (1) 2011: 343-350 - [c73]Kenji Nishida, Jun Fujiki, Takio Kurita:
Ensemble Random-subset SVM. IJCCI (NCTA) 2011: 334-339 - [c72]Takio Kurita:
Discriminant Kernels derived from the optimum nonlinear discriminant analysis. IJCNN 2011: 299-306 - 2010
- [j25]Rameswar Debnath, Takio Kurita:
An evolutionary approach for gene selection and classification of microarray data based on SVM error-bound theories. Biosyst. 100(1): 39-46 (2010) - [j24]Tetsu Matsukawa, Takio Kurita:
Extraction of Combined Features from Global/Local Statistics of Visual Words Using Relevant Operations. IEICE Trans. Inf. Syst. 93-D(10): 2870-2874 (2010) - [c71]Keiji Shimada, Tetsu Matsukawa, Yoshihiro Noguchi, Takio Kurita:
Appearance-Based Smile Intensity Estimation by Cascaded Support Vector Machines. ACCV Workshops (1) 2010: 277-286 - [c70]Tetsu Matsukawa, Takio Kurita:
Action Recognition Using Three-Way Cross-Correlations Feature of Local Moton Attributes. ICPR 2010: 1731-1734 - [c69]Kenji Nishida, Takio Kurita, Yasuo Ogiuchi, Masakatsu Higashikubo:
Visual Tracking Algorithm Using Pixel-Pair Feature. ICPR 2010: 1808-1811 - [c68]Tetsu Matsukawa, Takio Kurita:
Scene Classification using Spatial Relationship between Local Posterior Probabilities. VISAPP (2) 2010: 325-332
2000 – 2009
- 2009
- [j23]Takio Kurita:
Foreword. IEICE Trans. Inf. Syst. 92-D(7): 1337 (2009) - [c67]Epifanio Bagarinao, Takio Kurita, Masakatsu Higashikubo, Hiroaki Inayoshi:
Adapting SVM Image Classifiers to Changes in Imaging Conditions Using Incremental SVM: An Application to Car Detection. ACCV (3) 2009: 363-372 - [c66]Tetsu Matsukawa, Takio Kurita:
Image Classification Using Probability Higher-Order Local Auto-Correlations. ACCV (3) 2009: 384-394 - [c65]Rameswar Debnath, Takio Kurita:
An Evolutionary Gene Selection Method for Microarray Data Based on SVM Error Bound Theories. BIOCOMP 2009: 153-158 - [c64]Akinori Hidaka, Takio Kurita:
Co-occurrence of Intensity and Gradient Features for Object Detection. ICONIP (2) 2009: 38-46 - [c63]Tetsu Matsukawa, Akinori Hidaka, Takio Kurita:
Classification of Spectators' State in Video Sequences by Voting of Facial Expressions and Face Directions. MVA 2009: 426-430 - [c62]Takio Kurita, Kenji Watanabe, Nobuyuki Otsu:
Logistic discriminant analysis. SMC 2009: 2167-2172 - 2008
- [j22]Akinori Hidaka, Kenji Nishida, Takio Kurita:
Object Tracking by Maximizing Classification Score of Detector Based on Rectangle Features. IEICE Trans. Inf. Syst. 91-D(8): 2163-2170 (2008) - [c61]Akinori Hidaka, Takio Kurita, Nobuyuki Otsu:
Object Detection by Selective Integration of HLAC Mask Features. BLISS 2008: 46-50 - [c60]Kenji Watanabe, Takio Kurita:
Motion Recognition by Higher Order Local Auto Correlation Features of Motion History Images. BLISS 2008: 51-55 - [c59]Akinori Hidaka, Takio Kurita:
Non-Neighboring Rectangular Feature selection using Particle Swarm Optimization. ICPR 2008: 1-4 - [c58]Kenji Watanabe, Takio Kurita:
Locality preserving multi-nominal logistic regression. ICPR 2008: 1-4 - [c57]Kenji Watanabe, Takio Kurita:
RANSAC-SVM for large-scale datasets. ICPR 2008: 1-4 - [c56]Kenji Watanabe, Akinori Hidaka, Takio Kurita:
Automatic factorization of biological signals by using Boltzmann non-negative matrix factorization. IJCNN 2008: 1122-1128 - [c55]Akinori Hidaka, Takio Kurita:
Fast training algorithm by Particle Swarm Optimization and random candidate selection for rectangular feature based boosted detector. IJCNN 2008: 1163-1169 - [c54]Kenji Nishida, Takio Kurita:
Boosting with cross-validation based feature selection for pedestrian detection. IJCNN 2008: 1250-1256 - 2007
- [j21]Kazuro Shimokawa, Yuko Okamura-Oho, Takio Kurita, Martin C. Frith, Jun Kawai, Piero Carninci, Yoshihide Hayashizaki:
Large-scale clustering of CAGE tag expression data. BMC Bioinform. 8 (2007) - [j20]Toshio Tanaka, Kenji Nishida, Takio Kurita:
Navigation of mobile robot using location map of place cells and reinforcement learning. Systems and Computers in Japan 38(7): 65-75 (2007) - [j19]Hiroyuki Shimai, Takio Kurita, Shinji Umeyama, Masaru Tanaka, Taketoshi Mishima:
Adaptive background estimation based on robust statistics. Systems and Computers in Japan 38(7): 98-108 (2007) - [c53]Hiroaki Inayoshi, Takio Kurita:
Binarizing Training Samples with Multi-threshold for Viola-Jones Face Detector. ICONIP (2) 2007: 588-597 - [c52]Takuya Kobayashi, Akinori Hidaka, Takio Kurita:
Selection of Histograms of Oriented Gradients Features for Pedestrian Detection. ICONIP (2) 2007: 598-607 - [c51]Kenji Watanabe, Takio Kurita:
Automatic Factorization of Biological Signals Measured by Fluorescence Correlation Spectroscopy Using Non-negative Matrix Factorization. ICONIP (2) 2007: 798-806 - [c50]Kenji Nishida, Eisuke Adachi, Takio Kurita:
The recognition of a safe-overtaking driving environment. IFAC HMS 2007: 431-436 - [c49]Hiroaki Inayoshi, Takio Kurita:
Driver's head pose classification using a single video camera. IFAC HMS 2007: 437-442 - [c48]Kenji Tanaka, Takio Kurita, Tohru Kawabe:
Selection of Import Vectors via Binary Particle Swarm Optimization and Cross-Validation for Kernel Logistic Regression. IJCNN 2007: 1037-1042 - [c47]Eisuke Adachi, Hiroaki Inayoshi, Takio Kurita:
Estimation of Lane State from Car-mounted Camera Using Multiple-model Particle Filter Based on Voting Result for One-dimensional Parameter Space. MVA 2007: 323-326 - 2006
- [c46]Takio Kurita, Tatsuya Hosoi, Akinori Hidaka:
Principal Component Analysis of Multi-view Images for Viewpoint-Independent Face Recognition. AVSS 2006: 55 - [c45]Eisuke Adachi, Takio Kurita, Nobuyuki Otsu:
Reliability index of optical flow that considers error margin of matches and stabilizes camera movement estimation. ICPR (1) 2006: 699-702 - [c44]Akinori Hidaka, Kenji Nishida, Takio Kurita:
Face Tracking by Maximizing Classification Score of Face Detector Based on Rectangle Features. ICVS 2006: 48 - [c43]Kenji Tanaka, Takio Kurita, Friedrich Meyer, Luc Berthouze, Tohru Kawabe:
Stepwise Feature Selection by Cross Validation for EEG-based Brain Computer Interface. IJCNN 2006: 4672-4677 - [c42]Kenji Nishida, Takio Kurita:
Kernel Feature Selection to Improve Generalization Performance of Boosting Classifiers. IPCV 2006: 627-632 - 2005
- [j18]Takio Kurita, Toshiharu Taguchi:
A Kernel-Based Fisher Discriminant Analysis for Face Detection. IEICE Trans. Inf. Syst. 88-D(3): 628-635 (2005) - [j17]Kazuhiro Hotta, Masaru Tanaka, Takio Kurita, Taketoshi Mishima:
An Efficient Search Method Based on Dynamic Attention Map by Ising Model. IEICE Trans. Inf. Syst. 88-D(10): 2286-2295 (2005) - [j16]Takashi Takahashi, Takio Kurita:
A robust classifier combined with an auto-associative network for completing partly occluded images. Neural Networks 18(7): 958-966 (2005) - [c41]Kenji Nishida, Takio Kurita:
Boosting Soft-Margin SVM with Feature Selection for Pedestrian Detection. Multiple Classifier Systems 2005: 22-31 - [c40]