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Takio Kurita
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2020 – today
- 2024
- [j60]Shinji Uchinoura, Takio Kurita:
Improved Head and Data Augmentation to Reduce Artifacts at Grid Boundaries in Object Detection. IEICE Trans. Inf. Syst. 107(1): 115-124 (2024) - [j59]Motoshi Abe, Yuichiro Nomura, Takio Kurita:
Nonlinear dimensionality reduction with q-Gaussian distribution. Pattern Anal. Appl. 27(1): 26 (2024) - [c138]Zhicheng Zhang, Takio Kurita:
Tackling Background Misclassification in Box-Supervised Segmentation: A Background Constraint Approach. IW-FCV 2024: 1-13 - [c137]Eito Tada, Takio Kurita:
Clustering of Face Images in Video by Using Deep Learning. IW-FCV 2024: 14-26 - [c136]Kohei Fukuda, Takio Kurita, Hiroaki Aizawa:
Important Pixels Sampling for NeRF Training Based on Edge Values and Squared Errors Between the Ground Truth and the Estimated Colors. VISIGRAPP (2): VISAPP 2024: 102-111 - 2023
- [j58]Yuichiro Nomura, Takio Kurita:
Data Expansion Approach with Attention Mechanism for Learning with Noisy Labels. Int. J. Artif. Intell. Tools 32(1): 2350027:1-2350027:19 (2023) - [j57]Novanto Yudistira, Muthu Subash Kavitha, Jeny Rajan, Takio Kurita:
Attention-effective multiple instance learning on weakly stem cell colony segmentation. Intell. Syst. Appl. 17: 200187 (2023) - [j56]Shinji Uchinoura, Jun'ichi Miyao, Takio Kurita:
An Object Detection Method Using Probability Maps for Instance Segmentation to Mask Background. J. Adv. Comput. Intell. Intell. Informatics 27(5): 886-895 (2023) - [c135]Yin Wang, Hiroaki Aizawa, Takio Kurita:
Image Inpainting for Large and Irregular Mask Based on Partial Convolution and Cross Semantic Attention. ACPR (2) 2023: 115-128 - [c134]Kohei Fukuda, Takio Kurita, Hiroaki Aizawa:
Neural Radiance Fields with Regularizer Based on Differences of Neighboring Pixels. IJCNN 2023: 1-7 - [c133]Jiazhou Zheng, Hiroaki Aizawa, Takio Kurita:
Facial Image Manipulation via Discriminative Decomposition of Semantic Space. IJCNN 2023: 1-8 - 2022
- [j55]Yuichiro Nomura, Takio Kurita:
Consistency Regularization on Clean Samples for Learning with Noisy Labels. IEICE Trans. Inf. Syst. 105-D(2): 387-395 (2022) - [j54]Yuichiro Nomura, Takio Kurita:
Sample Selection Approach with Number of False Predictions for Learning with Noisy Labels. IEICE Trans. Inf. Syst. 105-D(10): 1759-1768 (2022) - [j53]Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita:
Weakly-Supervised Action Localization, and Action Recognition Using Global-Local Attention of 3D CNN. Int. J. Comput. Vis. 130(10): 2349-2363 (2022) - [j52]Qien Yu, Muthu Subash Kavitha, Takio Kurita:
Correction to: Extensive framework based on novel convolutional and variational autoencoder based on maximization of mutual information for anomaly detection. Neural Comput. Appl. 34(1): 821 (2022) - [c132]Hidenori Ide, Hiromu Fujishige, Jun'ichi Miyao, Takio Kurita:
Decomposition of Invariant and Variant Features by Using Convolutional Autoencoder. IW-FCV 2022: 97-111 - [c131]Simin Liu, Yuta Konishi, Jun'ichi Miyao, Takio Kurita:
Optimization of Re-ranking Based on k-Reciprocal for Vehicle Re-identification. IW-FCV 2022: 300-311 - [c130]Ramyaa Murugan, Jonathan Mojoo, Takio Kurita:
Supervised Learning for Convolutional Neural Network with Barlow Twins. ICANN (4) 2022: 484-495 - [c129]Jiazhou Zheng, Hiroaki Aizawa, Takio Kurita:
Additional Learning for Joint Probability Distribution Matching in BiGAN. ICONIP (1) 2022: 165-176 - [c128]Shinji Uchinoura, Takio Kurita:
Graph Laplacian Regularization based on the Differences of Neighboring Pixels for Conditional Convolutions for Instance Segmentation. ICPR 2022: 3611-3617 - [i18]Novanto Yudistira, Muthu Subash Kavitha, Jeny Rajan, Takio Kurita:
Attention-effective multiple instance learning on weakly stem cell colony segmentation. CoRR abs/2203.04606 (2022) - [i17]Huipeng Zheng, Lukman Hakim, Takio Kurita, Jun'ichi Miyao:
Single-Image Super-Resolution Reconstruction based on the Differences of Neighboring Pixels. CoRR abs/2212.13730 (2022) - [i16]Lukman Hakim, Takio Kurita:
Pixel Relationships-based Regularizer for Retinal Vessel Image Segmentation. CoRR abs/2212.13731 (2022) - 2021
- [j51]Qien Yu, Muthu Subash Kavitha, Takio Kurita:
Mixture of experts with convolutional and variational autoencoders for anomaly detection. Appl. Intell. 51(6): 3241-3254 (2021) - [j50]Jonathan Mojoo, Takio Kurita:
Deep Metric Learning for Multi-Label and Multi-Object Image Retrieval. IEICE Trans. Inf. Syst. 104-D(6): 873-880 (2021) - [j49]Qien Yu, Muthu Subash Kavitha, Takio Kurita:
Autoencoder framework based on orthogonal projection constraints improves anomalies detection. Neurocomputing 450: 372-388 (2021) - [j48]Qien Yu, Muthu Subash Kavitha, Takio Kurita:
Extensive framework based on novel convolutional and variational autoencoder based on maximization of mutual information for anomaly detection. Neural Comput. Appl. 33(20): 13785-13807 (2021) - [j47]Lukman Hakim, Muthu Subash Kavitha, Novanto Yudistira, Takio Kurita:
Regularizer based on Euler characteristic for retinal blood vessel segmentation. Pattern Recognit. Lett. 149: 83-90 (2021) - [c127]Motoshi Abe, Takio Kurita:
q-Softplus Function: Extensions of Activation Function and Loss Function by Using q-Space. ACPR (2) 2021: 31-44 - [c126]Gaojian Zhang, Takio Kurita:
Age Estimation from the Age Period by Using Triplet Network. IW-FCV 2021: 81-92 - [c125]Yuichiro Nomura, Takio Kurita:
Robust Training of Deep Neural Networks with Noisy Labels by Graph Label Propagation. IW-FCV 2021: 281-293 - [c124]Huipeng Zheng, Lukman Hakim, Takio Kurita, Jun'ichi Miyao:
Single-Image Super-Resolution Reconstruction Based on the Differences of Neighboring Pixels. ICONIP (5) 2021: 522-529 - [c123]Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
Parametric q-Gaussian distributed stochastic neighbor embedding with Convolutional Neural Network. IJCNN 2021: 1-7 - [c122]Michiaki Ueda, Keijiro Kanda, Jun'ichi Miyao, Shogo Miyamoto, Yukiko Nakano, Takio Kurita:
Invariant Feature Extraction for CNN Classifier by using Gradient Reversal Layer. SMC 2021: 851-856 - 2020
- [j46]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) - [j45]Hidenori Ide, Takumi Kobayashi, Kenji Watanabe, Takio Kurita:
Robust pruning for efficient CNNs. Pattern Recognit. Lett. 135: 90-98 (2020) - [j44]Novanto Yudistira, Takio Kurita:
Correlation Net: Spatiotemporal multimodal deep learning for action recognition. Signal Process. Image Commun. 82: 115731 (2020) - [c121]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 - [c120]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 - [c119]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 - [c118]Motoshi Abe, Jun'ichi Miyao, Takio Kurita:
q-SNE: Visualizing Data using q-Gaussian Distributed Stochastic Neighbor Embedding. ICPR 2020: 1051-1058 - [c117]Kakeru Mitsuno, Takio Kurita:
Filter Pruning using Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks. ICPR 2020: 1089-1095 - [c116]Kakeru Mitsuno, Yuichiro Nomura, Takio Kurita:
Channel Planting for Deep Neural Networks using Knowledge Distillation. ICPR 2020: 7573-7579 - [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]Michiaki 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
- [j43]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) - [j42]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
- [j41]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) - [j40]Motaz Sabri, Takio Kurita:
Facial expression intensity estimation using Siamese and triplet networks. Neurocomputing 313: 143-154 (2018) - [j39]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) - [j38]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
- [j37]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) - [j36]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) - [j35]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
- [j34]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
- [j33]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
- [j32]Zhouxin Yang, Takio Kurita:
Improvements of Local Descriptor in HOG/SIFT by BOF Approach. IEICE Trans. Inf. Syst. 97-D(5): 1293-1303 (2014) - [j31]Takashi Takahashi, Takio Kurita:
Image Classification Using a Mixture of Subspace Models. Inf. Media Technol. 9(3): 381-385 (2014) - [j30]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
- [j29]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) - [j28]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) - [j27]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]