九州大学-研究者情報 [松川徹 (助教) システム情報科学研究院情報学部門]

松川徹（まつかわてつ）

データ更新日：2024.03.26

助教　／　システム情報科学研究院情報学部門

原著論文

1.	Liheng Shen, Tetsu Matsukawa, Einoshin Suzuki, SATJiP: Spatial and Augmented Temporal Jigsaw Puzzles for Video Anomaly Detection, Proc. 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2024), -, 2024.05.
2.	Ryosuke Miyake, Tetsu Matsukawa, Einoshin Suzuki, Image Generation from Hyper Scene Graphs with Trinomial Hyperedges Using Object Attention, Proc. 19th International Conference on Vision Theory and Application (VISAPP2024), pp.266-279, 2024.02.
3.	Jose Alejandro Avellaneda Gonzalez, Tetsu Matsukawa, Einoshin Suzuki:, Cross-Modal Self-Supervised Feature Extraction for Anomaly Detection in Human Monitoring, Proc. of Nineteenth International Conference on Automation Science and Engineering (CASE 2023), pp.1-8, 2023.08.
4.	Ryosuke Miyake, Tetsu Matsukawa, Einoshin Suzuki, Image Generation from Hyper Scene Graphs with Trinomial Hyperedges, Proc. of 18th International Conference on Vision Theory and Application (VISAPP2023), 10.5220/0011699300003417, pp.185-195, 2023.02.
5.	Liheng Shen, Tetsu Matsukawa, Einoshin Suzuki, Detecting Video Anomalous Events with an Enhanced Abnormality Score, Proc. PRICAI 2022: Trends in Artificial Intelligence - 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2022), 2022.11.
6.	Yusuke Ohtsubo, Tetsu Matsukawa, Einoshin Suzuki, Semi-Supervised Few-Shot Classification with Deep Invertible Hybrid Models, arXiv, 2021.06.
7.	Muhammad Fikko Fadjrimiratno, Yusuke Hatae, Tetsu Matsukawa, Einoshin Suzuki, Detecting Anomalies from Human Activities by an Autonomous Mobile Robot Based on "Fast and Slow" Thinking", Proc. Sixteenth International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021), Vol. 5: VISAPP (Sixteenth International Conference on Computer Vision Theory and Applications), 943-953, 2021.02.
8.	Tetsu Matsukawa, Einoshin Suzuki, Convolutional Feature Transfer via Camera-specific Discrimative Pooling for Person Re-Identification, Proceedings of 25th International Conference on Pattern Recognition (ICPR2020), 8408-8415, 2021.01.
9.	Kaikai Zhao, Takashi Imaseki, HIroshi Mouri, Einoshin Suzuki, Tetsu Matsukawa , From Certain to Uncertain: Toward Optimal Solution for Offline Multiple Object Tracking, Proceedings of 25th International Conference on Pattern Recognition (ICPR2020), 2506-2513, 2021.01.
10.	Ning Dong, Yusuke Hatae, Muhammad Fikko Fadjrimiratno, Tetsu Matsukawa, Einoshin Suzuki, Experimental Evaluation of GAN-Based One-Classs Anomaly Detection on Office Monitoring, Proceedings of 25th International Symposium on Intelligent Systems (ISMIS2020), 214-224, 2020.09.
11.	Wenbo Li, Tetsu Matsukawa, Hiroto Saigo, Einoshin Suzuki, Context-Aware Latent Dirichlet Allocation for Topic Segmentation, 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, 10.1007/978-3-030-47426-3_37, 475-486, 2020.06, [URL].
12.	Hirofumi Fujita, Tetsu Matsukawa, Einoshin Suzuki, Detecting Outliers with One-Class Selective Transfer Machine, Knowledge and Information Systems (KAIS), DOI 10.1007/s10115-019-01407-5, 1-38, 2020.01, [URL].
13.	Yusuke Hatae, Qingpu Yang, Muhammad Fikko Fadjrimiratno, Yuanyuan Li, Tetsu Matsukawa, Einoshin Suzuki, Detecting anomalous regions from an image based on deep captioning, 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020 VISAPP, 326-335, 2020.02.
14.	Yusuke Ohtsubo, Tetsu Matsukawa, Einoshin Suzuki, Harnessing GAN with metric learning for one-shot generation on a fine-grained category, 31st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2019 Proceedings - IEEE 31st International Conference on Tools with Artificial Intelligence, ICTAI 2019, 10.1109/ICTAI.2019.00130, 915-922, 2019.11, [URL].
15.	Tetsu Matsukawa, Takahiro Okabe, Einoshin Suzuki, Yoichi Sato, Hierarchical Gaussian Descriptors with Application to Person Re-Identification, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 10.1109/TPAMI.2019.2914686, 1-14, 2019.05, [URL], ..
16.	Tetsu Matsukawa, Einoshin Suzuki, Kernelized cross-view quadratic discriminant analysis for person re-identification, Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019, 10.23919/MVA.2019.8757990, 2019.05, [URL].
17.	Kaikai Zhao, Tetsu Matsukawa, Einoshin Suzuki, Experimental validation for N-ary error correcting output codes for ensemble learning of deep neural networks, Journal of Intelligent Information Systems (JIIS), 52, 2, 367-392, 2019.04, [URL].
18.	Kaikai Zhao, Tetsu Matsukawa, Einoshin Suzuki, Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification, 24th International Conference on Pattern Recognition, ICPR 2018, 10.1109/ICPR.2018.8545535, 860-867, 2018.11, [URL].
19.	Soichiro Oura, Tetsu Matsukawa, Einoshin Suzuki, Multimodal Deep Neural Network with Image Sequence Features for Video Captioning, Proceedings of International Joint Conference on Neural Networks, IJCNN 2018, 10.1109/IJCNN.2018.8489668, 2018.10, [URL].
20.	Tetsu Matsukawa, Takahiro Okabe, Einoshin Suzuki, Yoichi Sato, Hierarchical Gaussian Descriptors with Application to Person Re-Identification, ArXiv, 1706.04318, 2017.06.
21.	Tetsu Matsukawa, Takahiro Okabe, Einoshin Suzuki, Yoichi Sato, Hierarchical Gaussian Descriptor for Person Re-identification, Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, 10.1109/CVPR.2016.152, 1363-1372, 2016.12, [URL].
22.	Hirofumi Fujita, Tetsu Matsukawa, Einoshin Suzuki, One-class selective transfer machine for personalized anomalous facial expression detection, Proceedings of 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, 10.5220/0006613502740283, 274-283, 2018.02, [URL].
23.	Tetsu Matsukawa, Einoshin Suzuki, Person re-identification using CNN features learned from combination of attributes, 23rd International Conference on Pattern Recognition, ICPR 2016, 10.1109/ICPR.2016.7900000, 2428-2433, 2016.12, [URL].
24.	Einoshin Suzuki, Shin Ando, Yutaka Deguchi, Hiroaki Ogata, Tetsu Matsukawa, Masanori Sugimoto, Toward a platform for collecting, mining, and utilizing behavior data for detecting students with depression risks, 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2015, 10.1145/2769493.2769538, 2015.07, [URL].

九大関連コンテンツ

pure2017年10月2日から、「九州大学研究者情報」を補完するデータベースとして、Elsevier社の「Pure」による研究業績の公開を開始しました。

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