2022

  • Jiazhou Zheng, Hiroaki Aizawa and Takio Kurita, “ Additional Learning for Joint Probability Distribution Matching in BiGAN,’’ Proc. of ICONIP2022, 2022. (accepted) 
  • Murugan, R., Mojoo, J., Kurita, T. (2022). Supervised Learning for Convolutional Neural Network with Barlow Twins. In: Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A., Aydin, M. (eds) Artificial Neural Networks and Machine Learning – ICANN 2022. ICANN 2022. Lecture Notes in Computer Science, vol 13532. Springer, Cham. https://doi.org/10.1007/978-3-031-15937-4_41
  • Shinji Uchinoura and Takio Kurita, “Graph Laplacian Regularization based on the Differences of Neighboring Pixels for Conditional Convolutions for Instance Segmentation,’’ Proc. of ICPR2022. 
  • Yuichiro Nomura and Takio Kurita, “Summary of Works on Image Classification with Noisy Labels,’’ 2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), 2022, pp. 1120-1124, doi: 10.23919/IPEC-Himeji2022-ECCE53331.2022.9807158.
  • Lukman Hakim and Takio Kurita, “Pixel Relationships-Based Regularizer for Retinal Vessel Image Segmentation,’’ 022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), 2022, pp. 1125-1129, doi: 10.23919/IPEC-Himeji2022-ECCE53331.2022.9806976.
  • Motoshi Abe and Takio Kurita, “ PatchNet: Patching Trained Model by Additional Neural Network,’’ Proc. of IW-FCV2022. 
  • Simin Liu, Yuta Konishi, Junichi Miyao and Takio Kurita, “ Optimization of Re-ranking based on k-reciprocal for Vehicle Re-identification,’’ In: Sumi, K., Na, I.S., Kaneko, N. (eds) Frontiers of Computer Vision. IW-FCV 2022. Communications in Computer and Information Science, vol 1578. Springer, Cham. https://doi.org/10.1007/978-3-031-06381-7_21
  • Hidenori Ide, Hiromu Fujishige, Junichi Miyao and Takio Kurita, “ Decomposition of Invariant and Variant Features by using Convolutional Autoencoder,’’ In: Sumi, K., Na, I.S., Kaneko, N. (eds) Frontiers of Computer Vision. IW-FCV 2022. Communications in Computer and Information Science, vol 1578. Springer, Cham. https://doi.org/10.1007/978-3-031-06381-7_7

2021

  • Huipeng Zheng, Lukman Hakim, Takio Kurita and Junichi Miyao, “ Single-Image Super-Resolution Reconstruction based on the Differences of Neighboring Pixels,’’ Proc. Of ICONIP2021. In: Mantoro T., Lee M., Ayu M.A., Wong K.W., Hidayanto A.N. (eds) Neural Information Processing. ICONIP 2021. Communications in Computer and Information Science, vol 1516. Springer, Cham. https://doi.org/10.1007/978-3-030-92307-5_61
  • Motoshi Abe and Takio Kurita, “ q-Softplus Function: Extensions of Activation Function and Loss Function by using q-Space,’’ In: Wallraven, C., Liu, Q., Nagahara, H. (eds) Pattern Recognition. ACPR 2021. Lecture Notes in Computer Science, vol 13189. Springer, Cham. https://doi.org/10.1007/978-3-031-02444-3_3
  • Michiaki Ueda, Keijiro Kanda, Junichi Miyao and Takio Kurita, Shogo Miyamoto, and Yukiko Nakano, “Invariant Feature Extraction for CNN Classifier by using Gradient Reversal Layer,’’ Proc. of SMC2021. 
  • Motoshi Abe, Junichi Miyao and Takio Kurita, “Parametric q-Gaussian distributed stochastic neighbor embedding with Convolutional Neural Network,” Proc. of IJCNN2021. 2021.07.
  • Gaojian Zhang and Takio Kurita, “Age Estimation from the Age Period by using Triplet Network,’’ Proc. Of IW-FCV2021, 2021.02.22.
  • Yuichiro Nomura and Takio Kurita, “Robust Training of Deep Neural Networks with Noisy Labels by Graph Label Propagation,’’ Proc. Of IW-FCV2021, 2021.02.23.

2020

  • Kakeru Mitsuno, Yuichiro Nomura, Takio Kurita, “Channel Planting for Deep Neural Networks using Knowledge Distillation,’’ Proc. of 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, Jan 10-15, 2020, pp.7573-7579, 2020.01.13.
  • Motoshi Abe, Junichi Miyao and Takio Kurita,“q-SNE: Visualizing Data using q-Gaussian Distributed Stochastic Neighbor Embedding,’’ Proc. of 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, Jan 10-15, 2020, pp.1051-1058, 2020.01.14.
  • Kakeru Mitsuno, Junichi Miyao and Takio Kurita, “ Filter Pruning using Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks,’’ Proc. of 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, Jan 10-15, 2020, pp.1089-1095, 2020.01.14.
  • Michiaki Ueda, Yuichiro Nomura, Junichi 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,’’ Proc. Of IEEE International Conference on Systems, Man, and Cybernetics (SMC), October 11-14, 2020. Toronto, Canada, pp.824-829. 2020.10.11-14.
  • Motoshi Abe, Junichi Miyao and Takio Kurita, “ Adaptive Neuron-wise Discriminant Criterion and Adaptive Center Loss at Hidden Layer for Deep Convolutional Neural Network,’’ Proc. of The International Joint Conference on Neural Networks (IJCNN), 2020.07.19-27.
  • Kakeru Mitsuno, Junichi Miyao and Takio Kurita, “ Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks,’’ Proc. of The International Joint Conference on Neural Networks (IJCNN), 2020.07.19-27.
  • Hideki Oki, Motoshi Abe, Junichi Miyao and Takio Kurita, “ Triplet Loss for Knowledge Distillation,’’ Proc. of The International Joint Conference on Neural Networks (IJCNN), 2020.07.19-27.

2019

  • Hakim, L., Yudistira, N., Kavitha, M., & Kurita, T. (2019, December). U-Net with Graph Based Smoothing Regularizer for Small Vessel Segmentation on Fundus Image. In International Conference on Neural Information Processing (pp. 515-522). Springer, Cham.
  • Mojoo, Jonathan, et al. “Learning with Incomplete Labels for Multi-label Image Annotation Using CNN and Restricted Boltzmann Machines.” International Conference on Neural Information Processing. Springer, Cham, 2019.
  • Oki, Hideki, Junichi Miyao, and Takio Kurita. “Siamese Network for Classification with Optimization of AUC.” International Conference on Neural Information Processing. Springer, Cham, 2019.
  • Loka, Nasrulloh RBS, Muthusubash Kavitha, and Takio Kurita. “Hilbert Vector Convolutional Neural Network: 2D Neural Network on 1D Data.” International Conference on Artificial Neural Networks. Springer, Cham, 2019.
  • Mojoo, Jonathan, Motaz Sabri, and Takio Kurita. “Video Super Resolution with Estimation of Motion Information by Using Higher Resolution Images Obtained by Single Image Super Resolution.” 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 2019.
  • Shuai, S., Kavitha, M., Miyao, J., & Kurita, T. Action Classification Based on 2D Coordinates Obtained by Real-time Pose Estimation. Proc. of The International Workshop on Frontiers of Computer Vision (IWFCV), 2019
  • Ye, Z., Kavitha, M., Miyao, J., & Kurita, T. Music score estimation algorithm using octave hierarchy defined on logarithmic frequency. Proc. of The International Workshop on Frontiers of Computer Vision (IWFCV), 2019

2018

  • Oki, Hideki, and Takio Kurita. “Mixup of Feature Maps in a Hidden Layer for Training of Convolutional Neural Network.” International Conference on Neural Information Processing. Springer, Cham, 2018.
  • Ide, Hidenori, and Takio Kurita. “Convolutional Neural Network with Discriminant Criterion for Input of Each Neuron in Output Layer.” International Conference on Neural Information Processing. Springer, Cham, 2018.
  • Indraswari, R., Kurita, T., Arifin, A. Z., Suciati, N., Astuti, E. R., & Navastara, D. A. (2018, December). 3D Region Merging for Segmentation of Teeth on Cone-Beam Computed Tomography Images. In 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS) (pp. 341-345). IEEE.
  • Yamada, R., Ide, H., Yudistira, N., & Kurita, T. (2018, August). Texture Segmentation using Siamese Network and Hierarchical Region Merging. In 2018 24th International Conference on Pattern Recognition (ICPR) (pp. 2735-2740). IEEE.

2017

  • Fujishige, Hiromu, Junichi Miyao, and Takio Kurita. “Image inpainting by recursive estimation using neural network and wavelet transformation.” International Conference on Neural Information Processing. Springer, Cham, 2017.
  • Mojoo, Jonathan, Keiichi Kurosawa, and Takio Kurita. “Deep CNN with Graph Laplacian Regularization for Multi-label Image Annotation.” International Conference Image Analysis and Recognition. Springer, Cham, 2017.
  • Yudistira, Novanto, and Takio Kurita. “Temporal evolution of motion superpixel for video classification.” 2017 3rd IEEE International Conference on Cybernetics (CYBCONF). IEEE, 2017.
  • Ide, Hidenori, and Takio Kurita. “Improvement of learning for CNN with ReLU activation by sparse regularization.” 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2017.

~ 2016

  • Ide, Hidenori, and Takio Kurita. “Low level visual feature extraction by learning of multiple tasks for Convolutional Neural Networks.” 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016.
  • Li, Ran, Xuezhen Li, and Takio Kurita. “Soft local binary patterns.” 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR). IEEE, 2015.
  • Yudistira, Novanto, and Takio Kurita. “Multiresolution local autocorrelation of optical flows over time for action recognition.” 2015 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, 2015.
  • Li, Xuezhen, and Takio Kurita. “Nonlinear discriminant analysis using K nearest neighbor estimation.” 2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV). IEEE, 2015.

・Zhibin Zhang, Zuezhen Li, Takio Kurita, and Shinya Tanaka, “ Pixel-Pair Features Selection for Vehicle Tracking,’’ The 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), November 5-8, 2013, Okinawa, Japan, pp.471-475, 2013.11.07. 

・Zhouxin Yang, and Takio Kurita, “ Improvements to the descriptor of SIFT by BOF approaches,’’ The 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), November 5-8, 2013, Okinawa, Japan, pp.95-99, 2013.11.07. 

・Takio Kurita, Kenji Watanabe, and Akinori Hidaka, “ Sparse Logistic Discriminant Analysis,’’ Prof. of IEEE International Conference on System, Man, and Cybernetics, October 13-16, 2013, Manchester, UK. 

・Xiaoying GUO, Takio KURITA, Chie MURAKI ASANO, Akira ASANO, “Visual complexity assessment of painiting images,’’ Proc. of ICIP2013. 

・Zhouxin Yang, and Takio Kurita, “BOG: an extension of HOG by interpreting it as bag of features,’’ Proc. of MAV2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN, pp.415-418, 2013.05. 

・Xinoying Guo, Chie Muraki Asano, Akira Asano, Takio Kurita, “Modeling Visual Complexity of Textures Associated with Texture Characteristics, 2012 International,” Conference of Information Science and Computer Applications (ICISCA 2012), Bali Indonesia from 19 -20 November 2012. published in Advances in Information Technology and Applied Computing, (ISSN 2251-3418), Vol.1, pp.121-126, 2012. 

・Takahishi Takeda, Toru Tamaki*, Bisser Raytchev,　Kazufumi Kaneda, Takio Kurita, Shigeto Yoshida, Yoshito Takemura, Keiichi Onji, Rie Miyaki, Shinji Tanaka, “Self-training with unlabeld regions for NBI image recognition,” Prof. of 21st International Conference on Pattern Recognition (ICPR 2012) November 11-15, 2012. Tsukuba, Japan, pp.25-28. 

・Akinori Hidaka and Takio Kurita, “Sparse Discriminant Analysis Based on the Bayesian Posterior Probability Obtained by L1 Regression,” Proc. of Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012) Miyajima-Itsukushima, Hiroshima, 7th-9th November, 2012. pp.648-656. 

・M.S.Kavitha, Takio Kurita, Akira Asano, and Akira Taguchi, “Automatic Assessment of Mandibular Bone Using Support Vector Machine for the Diagnosis of Osteoporosis,” Proc. of 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC2012), October 14-17, 2012, COEX, Seoul, Korea, pp.214-219, 2012.10.15. 

・Kenji Nishida, Jun Fujiki, Takumi Kobayashi, Chikao Tsuchiya, Shinya Tanaka, and Takio Kurita, “ Road Region Detection by Spatio-Temporal Graph Segmentation of Optical Flows using On-Board Camera,” Proc. of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA2012), 778-022, 2012.06.18. 

・Guo Xiaoyingm, Akira Asano, Chie Muraki Asano and Takio Kurita, “Objective Analysis of Visual Complexity Perception to the Texture Images,” International Conference on Kansei Engineering and Emotion Research, 22-25 May, 2012 Penghu, Taiwan, 2012. pp.216-224, 2012.05.23. 

・Chikao Tsuchiya , Shinya Tanaka and Hiroyuki Furusho (Nissan), Kenji Nishida (AIST), Takio Kurita (Hiroshima University), “Real-Time Vehicle Detection using a Single Rear Camera for a Blind Spot Warning System,” SAE 2012 World Congress & Exhibition, 2012. Detroit. 2012.04.25. 

・Akinori Hidaka, and Takio Kurita, “Discriminant Kernels based Support Vector Machine,” The First Asian Conference on Pattern Recognition (ACPR’11), November 28‐30, 2011, Beijing, China. 

・Tetsu Matsukawa, and Takio Kurita, “Discriminant Appearance Weighting for Action Recognition,” The First Asian Conference on Pattern Recognition (ACPR’11), November 28‐30, 2011, Beijing, China. 

・Kenji Nishida, and Takio Kurita, “Ensemble Random-Subset SVM,” the International Joint Conference on Computational Intelligence (NCTA2011), 24-26 October, 2011, Paris, France, pp.334-339, 2011.10.24. 

・Yasuo Ogiuchi, Masakatsu Higashikubo, Yuuki Ono, Takio Kurita and Kenji Nishida,“ Robust and Precise Measurement Method of Vehicles ans Motorcycles for Cooperative Driving Safety Support System with Combination of HOG-SVM Detection and Discreminative Pixel-Pair Tracking,” 18th ITS World Congress on Intelligent Transportation Systems, Orland, Oct.16-20, 2011.10.20. 

・Xiaoying Guo, Chie Muraki Asano, Akira Asano and Takio Kurita, “Visual Complexity Perception and Texture Image Characteristics,” 2011 International Conference on Biometrics and Kansei Engineering (ICBAKE 2011), pp.260-265, Kagawa University, Kagawa, Japan, Sep.19-22, 2011. 

・Kenji Nishida, Jun Fujiki and Takio Kurita, “Multiple Random Subset-Kernel Learning,” 14th International Conference on Computer Analysis of Images and Patterns (CAIP2011), Seville (Spain), 29-31 August 2011. 

・Takio Kurita, “Discriminant kernel derived from the optimum nonlinear discriminant analysis,” Proceedings of International Joint Conference on Neural Networks (IJCNN2011), San Jose, California, USA, July 31 – August 5, 2011, pp.299-306. 2011.08.4. 

・Kenji Nishida, Jun Fujiki, Chikao Tsuchiya, Shinya Tanaka, and Takio Kurita, “Road Plane Detection using Differential Homography Estimated by Pair Feature Matching of Local Regions,” the IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (SPPRA2011), February 16 – 18, 2011 Innsbruck, Austria. 

・Keiji Shimada, Yoshihiro Noguchi, Tetsu Matsukawa and Takio Kurita, “ Appearance-Based Smile Intensity Estimation by Cascaded Support Vector Machines,” Proc. of The 2nd International Workshop on Video Event Categorization, Tagging and Retrieval, November 8-12, 2010, Queenstown, New Zealand. 

・Tetsu Matsukawa and Takio Kurita,“Action recognition using three-way cross-correlations feature of local motion attributes,” Proc. of Inter. Conf. on Pattern Recognition (ICPR2010), pp.1731-1734, 2010.08. 

・Kenji Nishida, Takio Kurita, Yasuo Ogiuchi, and Masakatsu Higashikubo, “ Visual Tracking Algorithm using Pixel-Pair Feature,” Proc. of Inter. Conf. on Pattern Recognition (ICPR2010), pp.1808-1811, 2010.08. 

・Tetsu Matsukawa, and Takio Kurita, “Scene classification using spatial relationship between local posterior probabilities,” Proc. of International Conference on Computer Vision Theory and Applications (VISAPP2010), Vol.2, pp.325-332, 17-20 May, 2010. Angers, France. 

・Rameswar Debnath and Takio Kurita, “A comparison of evolutionary methods based on SVM error bound theories for multicategory microarray gene expression data,” Proc. of the International Multi-Conference on Complexity, Informatics and Cybernatics, Florida, USA, April 6-9, pp.295-299, 2010 (Session’s Best Paper Award).