Tokushima University / Educator and Researcher Directory --- Oono, Masaki

Field of Study

○	Intelligent Informatics

Subject of Study

○	Music Informaion Retrieval

Book / Paper

Book:

1.	Kenji Kita, Kazuyuki Matsumoto, Minoru Yoshida, Masami Shishibori and Masaki Oono : Hands-on Data Preprocessing in AI and Machine Learning, --- Data Science with Python ---, Kagakujyoho Shuppan Co., Ltd., Tokyo, Aug. 2021. (Summary) Research on artificial intelligence (AI) itself has been going on since the dawn of computing, with the "first AI boom" in the late 1950s and 1960s, the "second AI boom" in the 1980s and 1990s, and now we are in the midst of the "third AI boom". The major difference between this third boom and the previous first and second booms is the emergence of intelligent information processing systems that approach human capabilities in many fields. This can be attributed to a variety of factors, but the most significant are the accumulation of various kinds of big data, the accelerated progress of IT technologies that make such big data available, and the emergence of new machine learning paradigms such as deep learning. One of the keys to the success of AI and machine learning systems is the pre-processing of data. The essence of machine learning is to correctly make predictions and inferences about unknown data by learning the structure, regularities, and universality that lie behind large amounts of data. However, if the quality of the data used for learning is poor, the system will not be able to learn correctly, and the resulting system will not be accurate. In order to build a highly accurate system, it is important to eliminate poor data and process the data to convert it into a form that is easy to learn. This is exactly what preprocessing is responsible for. In extreme cases, it can be said that the success or failure of preprocessing guarantees the quality of the entire machine learning system. According to one theory, in the field of AI and machine learning system development, 60 to 80% of the time spent by engineers is spent on data collection and preprocessing. For efficient system development, it is essential to master preprocessing techniques. This book specifically focuses on preprocessing techniques, which have not been sufficiently covered in conventional books on machine learning and data science, and aims to be a practical book that allows readers to understand the techniques not only by explaining them, but also by actually running programs. The sister volume of this book, "Fundamentals," introduces basic preprocessing techniques. This book, "Applications," explains more advanced preprocessing techniques and preprocessing techniques for media data such as text, images, sound, and music. (Keyword) artificial intelligence / machine learning / Python / Preprocessing / data analysis / data mining / Google Colab / Big Data / Feature Selection / Dimensionality Reduction / NumPy / pandas / scikit-learn / matplotlib / TensorFlow / Keras / Data Cleaning / Feature Extraction / Scaling / Standardization / normalization / Normalization / Data Cleansing / Data Augmentation / Binning / Discretization / Categorical Data / Category Data / One-hot Encoding / One-hot Vector / Label Encoding / Frequency Encoding / Count Encoding / Ranked Frequency Encoding / Label-count Encoding / Feature Hashing / Global Hashing Space / Per-field Hashing Space / MurmurHash3 / Entity Embedding / Distributed Representation / Embedding / Table2Vec / Imbalanced Data / Resampling / Undersampling / Downsampling / Oversampling / Upsampling / Random Oversampling / Random Undersampling / ENN / SMOTE / ADASYN / Time-series Data / Point Process / Windowed Statistics / Aozora Bunko / Word Segmentation / morphological analysis / MeCab / Bigram / Trigram / N-gram / SentencePiece / Stop Word / Stop Word List / vector space model / Bag-of-Words / tf-idf / gensim / Topic Model / LDA / Gibbs Sampling / word2vec / Skip-gram / Continuous Bag-of-Words / Negative Sampling / Hierarchical Softmax / CNN / Forward Propagation / Activation Function / Back Propagation / Sum of Squares Error / Cross Entropy / Epoch / Gradient Descent / Batch Learning / Online Learning / Mini-batch Learning / iteration / Convolution Layer / Pooling Layer / Fully Connected Layer / Feature Map / Zero Padding / Maximum Pooling / Average Pooling / Dropout Layer / SDG / Shear Mapping / Fine-tuning / VGG16 / Sampling Rate / Quantization Bit Rate / Cocktail-party Effect / Spectral Subtraction / Harmonic/Percussive Sound Separation / Short-time Fourier Transform / Inverse Short-time Fourier Transform / Wiener Filter / Audio Source Separation
2.	Masaki Hashizume, Koichi Ute, Yumiko Izaki, Masaki Oono, Susumu Nakano, Akira Mizobuchi, Junji Tamatani, Naoyuki Shimomura, Takao Ueda, Katsutoshi Ueno, Fumiaki Nagao, Chikanori Hashimoto, Yasunori Muto, Takeshi Watanabe, Takahiro Kido, Tetsuro Katayama, Yoko Yamashita, Atsushi Tabata, Yuka Sasaki, 島木美香, Takeshige Otoi, Kaori Kanemaru, Takefumi Hattori, Tatsuo Hamano, Katsuyuki Miyawaki, Ryo Anma, Ken-ichi Nishiyama and Mutsuki Aoya : 安全マニュアル, Apr. 2021.

Academic Paper (Judged Full Paper):

1.	Katsumi Nagata, Masaki Oono and Masami Shishibori : The Development of a Hand-Washing Support System Using Image Processing Techniques, International Journal of Advanced Intelligence (IJAI), Vol.11, No.1, 1-13, 2020. (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1010572092265929728 (CiNii: 1010572092265929728)
2.	Masahiro Niitsuma, Masaki Matsubara, Masaki Oono and Hiroaki Saito : Development of a method for automatic basso continuo playing, Information Processing & Management, Vol.47, No.3, 440-451, 2011. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ipm.2010.11.001 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-79953246926 (DOI: 10.1016/j.ipm.2010.11.001, Elsevier: Scopus)
3.	Masaki Oono, Atlam EL-Sayed, Masao Fuketa, Kazuhiro Morita and Jun-ichi Aoe : A compressed trie structure using divided keys, International Journal of Computer Applications in Technology, Vol.34, No.2, 101-107, 2009. (Summary) We present a data structure to retrieve compound words efficiently. Compound words are created by combining in infinitum. Purpose of this research is to improve the space efficiency by dividing keys based on double array structure. (Link to Publication Site) ● Publication site (DOI): 10.1504/IJCAT.2009.023615 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1504/IJCAT.2009.023615 (DOI: 10.1504/IJCAT.2009.023615)
4.	Susumu Yata, Masaki Oono, Kazuhiro Morita, Masao Fuketa and Jun-ichi Aoe : An efficient deletion method for a minimal prefix double array, Software: Practice and Experience, Vol.37, No.5, 523-534, 2007. (Summary) A minimal prefix (MP) double array is an efficient data structure for a trie. However, the space efficiency of the MP double array is degraded by deletion. This paper presents a fast and compact adaptive deletion algorithm for the MP double array. The presented method is implemented with C. (Keyword) trie search / dictionary / information retrieval / SEARCH (Link to Publication Site) ● Publication site (DOI): 10.1002/spe.778 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/spe.778 (DOI: 10.1002/spe.778)
5.	Susumu Yata, Masaki Oono, Kazuhiro Morita, Masao Fuketa, Toru Sumitomo and Jun-ichi Aoe : A compact static double-array keeping character codes, Information Processing & Management, Vol.43, No.1, 237-247, 2007. (Summary) A trie represented by a double-array enables us to search a key fast with a small space. However, the double-array uses extra space to be updated dynamically. This paper presents a compact structure for a static double-array. The new structure keeps character codes instead of indices in order to compress elements of the double-array. In addition, the new structure unifies common suffixes and consists of less elements than the old structure. Experimental results for English keys show that the new structure reduces space usage of the double-array up to 40%. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ipm.2006.04.004 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.ipm.2006.04.004 (DOI: 10.1016/j.ipm.2006.04.004)
6.	Susumu Yata, Masaki Oono, Kazuhiro Morita, Masao Fuketa, Tomoko Yoshinari and Jun-ichi Aoe : 接頭辞ダブル配列における空間効率を低下させないキー削除法, Transactions of Information Processing Society of Japan, Vol.47, No.6, 1894-1902, 2006. (Summary) Minimal Prefix (MP) double-array represents a trie with two advantages - a fast retrieval and a compact dictionary. However, a key deletion produces empty elements and degrades the space efficiency of MP double-array. In addition, the deletion speed of MP double-array is degraded by the key deletion because the deletion time depends on the number of empty elements. This paper presents an efficient deletion method for MP double-array. The method dynamically removes keys from MP double-array without increasing empty elements. From experimental results for the key set which consists of 100,000 keys, it turned out that the presented method is about 17-460 times faster than the conventional method and maintains high space efficiency. (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1050001337882545536 (CiNii: 1050001337882545536)
7.	Yuki Kadoya, Kazuhiro Morita, Masao Fuketa, Masaki Oono, El-Sayed Atlam, Toru Sumitomo and Jun-ichi Aoe : A Sentence Classification Technique Using Intention Association Expressions, International Journal of Computer Mathematics, Vol.82, No.7, 777-792, 2005. (Summary) Although there are many text classification techniques depending on the vector space, it is difficult to detect the meaning related to the user's intention (complaint, encouragement, request, invitation, etc.). We present a technique for determining the speaker's intention for sentences in conversation. Intention association expressions are introduced, and formal descriptions with weights are defined using these expressions to construct an intention classification. A deterministic multi-attribute pattern-matching algorithm is used to determine the intention class efficiently. In simulation results for 681 email messages of 5,859 sentences, the multi-attribute pattern-matching algorithm is about 44.5 times faster than the Aho and Corasick method. (Link to Publication Site) ● Publication site (DOI): 10.1080/00207160412331336071 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1080/00207160412331336071 (DOI: 10.1080/00207160412331336071)
8.	Shinkaku Kashiji, El-Sayed Atlam, Masao Fuketa, Masaki Oono, Kazuhiro Morita, Kazuhiko Tsuda and Jun-ichi Aoe : A High-speed Dynamic Full-Text Search Method by Using Memory Management, International Journal of Computer Mathematics, Vol.81, No.12, 1477-1492, 2004. (Summary) This paper proposes an adaptive block management algorithm that is efficient for dynamic data management method. The new method speeds up character string retrieval by first making a full-text search of uni-gram and a full-text search of bi-gram. This paper proposes a method for enhancing the static full-text search system of bi-gram to the dynamic full-text search system of bi-gram. (Keyword) full-text search / inverted file search / uni-gram index / bi-gram index / adaptive block management / algorithm (Link to Publication Site) ● Publication site (DOI): 10.1080/00207160412331296643 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1080/00207160412331296643 (DOI: 10.1080/00207160412331296643)
9.	Kazuhiro Morita, Atlam EL-Sayed, Masao Fuketa, Kazuhiko Tsuda, Masaki Oono and Jun-ichi Aoe : Word classification and hierarchy using co-occurrence word information, Information Processing & Management, Vol.40, No.6, 957-972, 2004. (Summary) In the natural language processing system, dictionary is necessary and indispensable because the ability of the entire system is controlled by the amount and the quality of the dictionary. In this paper, the importance of co-occurrence word information in the natural language processing system is described. The classification technique of the co-occurrence word and the co-occurrence frequency is described and the classified group is expressed hierarchically. Moreover, this paper proposes a technique for an automatic construction system and a complete thesaurus. Experimental test operation of this system and effectiveness of the proposal technique is verified. (Link to Publication Site) ● Publication site (DOI): 10.1016/j.ipm.2003.08.009 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/j.ipm.2003.08.009 (DOI: 10.1016/j.ipm.2003.08.009)
10.	Masaki Oono, Masao Fuketa, Kazuhiro Morita, Shinkaku Kashiji and Jun-ichi Aoe : An Improvement Key Deletion Method for Double-Array Structure using Single-nodes, Information Processing & Management, Vol.40, No.1, 47-63, 2004. (Summary) The drawback of the double-array is that the space efficiency degrades by empty elements produced in key deletion. The space efficiency of old method is low for high frequent deletion and deletion takes much time because the cost depends on the number of the empty elements. This paper presents a fast and compact deletion method by using the property of nodes of single. (Keyword) dictionary retrieval / information retrieval / trie search / double-array structure / natural language processing / search (Link to Publication Site) ● Publication site (DOI): 10.1016/S0306-4573(02)00090-0 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1016/S0306-4573(02)00090-0 (DOI: 10.1016/S0306-4573(02)00090-0)
11.	Masaki Oono, Atlam EL-Sayed, Masao Fuketa, Kazuhiro Morita and Jun-ichi Aoe : A Fast and Compact Elimination Method of Empty Elements from a Double-Array Structure, Software: Practice and Experience, Vol.33, No.13, 1229-1249, 2003. (Summary) This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30-330 times faster than the conventional elimination method and maintains high space efficiency. (Keyword) dictionary / information retrieval / trie search / natural language processing / search (Link to Publication Site) ● Publication site (DOI): 10.1002/spe.545 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1002/spe.545 (DOI: 10.1002/spe.545)
12.	Masaki Oono, Kazuhiro Morita, Masao Fuketa and Jun-ichi Aoe : ダブル配列におけるキー削除の効率化手法, Transactions of Information Processing Society of Japan, Vol.44, No.5, 1311-1320, 2003. (Summary) ダブル配列構造の欠点はキーの削除によって生じる未使用要素により空間効率が低下する点である．本論文ではトライの兄弟を持たない節が多く，これらの節の遷移は容易に変更できるという特徴を利用し，削除を連続した場合でも空間使用率と削除速度を悪化させない効率的なキー削除手法を提案する．10万語の英単語に対する実験より，削除を連続した場合でも98%以上の空間使用率を維持でき，従来手法より約300倍高速に削除できることを実証した． (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1050564287837279872 (CiNii: 1050564287837279872)
13.	Masami Shishibori, Samuel Sangkon Lee, Masaki Oono and Jun-ichi Aoe : Improvement of the LR Parsing Table and Its Apprication to Grammatical Error Correction, International Journal of Informantion Sciences, Vol.Vol. 148, No.Issues 1-4, 11-26, 2002.
14.	Kazuhiro Morita, Masao Fuketa, Masaki Oono and Jun-ichi Aoe : ダブル配列における動的更新の効率化アルゴリズム, Transactions of Information Processing Society of Japan, Vol.42, No.9, 2229-2238, 2001. (Summary) キー検索技法の一つであるダブル配列は，動的更新の速度が問題となっている．本論文では，追加を高速化する手法と，削除時に生じる未使用要素の詰め直しを行う手法を提案する．10万語のキーを用いた実験を行い，本手法の有効性を実証した
15.	TeaHun Lee, Kazuaki Ando, Masaki Oono and Jun-ichi Aoe : A Method of Deriving Keywords Using Generation Rules of Compound Words, The Transactions of the Institute of Electronics, Information and Communication Engineers D-II, Vol.J84-DII, No.4, 812-821, 2001. (Summary) 本論文では，文書を読むための判断材料となる要約キーワードの導出を目的に，複合語生成規則を用いて文書中に陽に現れないキーワードを導出する手法を提案した．本手法を実現するために，係り受け関係に基づく規則と概念を利用した規則を構築した． (Keyword) 自動文書要約 / 複合語キーワード導出 / 係り受け関係 / 概念共起 / 生成規則 (Link to Search Site for Scientific Articles) ● CiNii @ National Institute of Informatics (CRID): 1520572359354590464 (CiNii: 1520572359354590464)
16.	Masafumi Koyama, Masaki Oono, Kazuhiro Morita and Jun-ichi Aoe : A Fast and Compact Technique of Implementing Transition Tables for Finite State Automata, Information Sciences, Vol.129, No.1-4, 141-154, 2000. (Summary) This paper proposes a method of compressing the triple-array structures. Although the approach is not optimal, it does realize a reasonable reduction in size. From the simulation results, it is verified that the presented method can produce fast and compact structures. (Link to Publication Site) ● Publication site (DOI): 10.1016/S0020-0255(00)00060-8 (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0034315626 (DOI: 10.1016/S0020-0255(00)00060-8, Elsevier: Scopus)

Proceeding of International Conference:

1.	Harumi Kadota, Shoma Fujisawa, Masaki Oono, Ryoma Morigaki, Nobuaki Yamamoto, Yasuhisa Kanematsu, Manabu Ishihara and Masami Shishibori : Development of a 3D visualization system for the cerebral aneurysm coil embolization, Proceedings Volume 11794, Fifteenth International Conference on Quality Control by Artificial Vision; 117940C (2021), Tokushima, Jul. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2589084 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1117/12.2589084 (DOI: 10.1117/12.2589084)
2.	Ryota Nishio, Masaki Oono, Takaharu Goto, Takahiro Kishimoto and Masami Shishibori : A reconstruction method of 3D face model from front and side 2D face images using deep learning model, Proceedings Volume 11794, Fifteenth International Conference on Quality Control by Artificial Vision; 1179406 (2021), Tokushima, Jul. 2021. (Link to Publication Site) ● Publication site (DOI): 10.1117/12.2588983 (Link to Search Site for Scientific Articles) ● Search Scopus @ Elsevier (DOI): 10.1117/12.2588983 (DOI: 10.1117/12.2588983)
3.	Katsumi Nagata, Masaki Oono and Masami Shishibori : The Development of a Hand-Washing Education System, Proceedings of the 27th International Conference on Computers in Education (ICCE2019), 225-229, Kenting, Taiwan, Dec. 2019. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-85077708614 (Elsevier: Scopus)
4.	Masaki Oono : A method for extracting influential nodes while considering the development of social networks, Proceedings of the international conference on social computing and its applications, Nov. 2012.
5.	Masahiro Niitsuma, Hiroshi Takaesu, Hazuki Demachi, Masaki Oono and Hiroaki Saito : Development of an Automatic Music Selection System Based on the Runners Step Frequency, Proceedings of international conference on music information retrieval, Sep. 2008.
6.	Susumu Yata, Masaki Oono, Kazuhiro Morita, Toru Sumitomo and Jun-ichi Aoe : Double-Array Compression by Pruning Twin Leaves and Unifying Common Suffixes, Proceedings of International Conference on Computing and Informatics (ICOCI 2006), Kuala Lumpur, Malaysia, Jun. 2006.
7.	Masaki Oono, Masao Fuketa, Kazuhiro Morita, Yutaka Inada, Yo Murakami and Jun-ichi Aoe : A Compression Method Using Link-Trie Structure for Natural Language Dictionaries, Proceedings of International Conference on Computing and Informatics (ICOCI 2006), Kuala Lumpur, Malaysia, Jun. 2006.
8.	Kazuhiro Morita, Atlam EL-Sayed, Masao Fuketa, Elmarhomy Ghada, Masaki Oono, Toru Sumitomo and Jun-ichi Aoe : New Approach for Speeding-up Technique of the Retrieval Using Dynamic Full-Text Search Algorithm, Proceedings of 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2005), Vol.4, 619-625, Melbourne, Sep. 2005.
9.	Shinkaku Kashiji, Toru Sumitomo, Kazuhiro Morita, Masaki Oono, Masao Fuketa and Jun-ichi Aoe : A Fast Dynamic Method Using Memory Management, Proceedings of 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2004), 558-566, Wellington, New Zealand, Sep. 2004.
10.	Masaki Oono, Kazuhiro Morita, Masao Fuketa, Mikio Oda, Jun Harada and Jun-ichi Aoe : An Efficient Key Updating Algorithm for Double-Array Structure, Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics (SCI2003), Vol.12, 311-313, Orlando, Jul. 2003.
11.	Masaki Oono, Kazuhiro Morita, EL-Sayed Atlam, Yuki Kadoya and Jun-ichi Aoe : A New Compact Deletion Algorithm for Double-Array Structures, Proceedings of 2002 IEEE International Conference on Systems, Man, and Cybernetics, Vol.4, 577-582, Hammamet, Tunisia, Oct. 2002. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0036967133 (Elsevier: Scopus)
12.	Masao Fuketa, EL-Sayed Atlam, Kazuhiro Morita, Masaki Oono and Jun-ichi Aoe : A Compression Algorithm Using Integrated Record Information for Translation Dictionaries, Proceedings of 2002 IEEE International Conference on Systems, Man, and Cybernetics, Vol.4, 588-593, Hammamet, Tunisia, Oct. 2002. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0036968758 (Elsevier: Scopus)
13.	Masao Fuketa, Masaki Oono, Kazuhiro Morita and Jun-ichi Aoe : On the Construction of Reduced Double Array Structures by Dividing Tries, Proceedings of 2001 IEEE International Conference on Systems, Man, and Cybernetics, 500-505, Tucson, Arizona, USA, Oct. 2001. (Link to Search Site for Scientific Articles) ● Summary page in Scopus @ Elsevier: 2-s2.0-0035725622 (Elsevier: Scopus)
14.	El-sayed Atlam, Masaki Oono, Kazuhiro Morita, Masao Fuketa and Jun-ichi Aoe : Similarity Measurement using Two Objects Weight Function, Proceedings of 5th International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies (KES'2001), 596-600, Osaka, Sep. 2001.

Proceeding of Domestic Conference:

1.	Manami Abe, 瀬分宏美, Tatsunao Sueuchi, Masahiro Sogabe, Masaki Oono, Masami Shishibori, Masao Fuketa, Kenji Terada, Hiroyuki Ueda and Toshiya Okahisa : 健診受診者を対象とした睡眠中の腸蠕動音解析システムの開発., 第61回日本人工臓器学会大会, Nov. 2023.
2.	Sobu Suzuki, 今村美和子, Tatsunao Sueuchi, Masahiro Sogabe, Masaki Oono, Masami Shishibori, Masao Fuketa, Kenji Terada, Hiroyuki Ueda and Toshiya Okahisa : 音楽聴収ストレス負荷試験による腸蠕動音と自律神経の変化., 第61回日本人工臓器学会大会, Nov. 2023.
3.	Hiroki Kojima, TAKUYA Taniguchi, KAWAHARADA Rie, Takeshi Oya, Koichi Tsuneyama, Masaki Oono and Masami Shishibori : 細胞診断システムにおける円形度に着目した領域分割の改善, 2023年電気学会電子・情報・システム部門大会, PS1-10, Aug. 2023.
4.	YUTO Nakai, Yusuke Takata, Ryoji Miyamoto, 石嵜雄一, 荒井健太, 青木仁史, 大津朋也, Kenzo Yamaguchi, Masaki Oono and Masami Shishibori : 光技術と深層学習を用いた枝豆内の異物検知, 2023年電気学会電子・情報・システム部門大会, PS1-8, Aug. 2023.
5.	TOMOKI Uchiyama, Ryoji Miyamoto, 大津朋也, Kenzo Yamaguchi, Masaki Oono and Masami Shishibori : 機械学習を用いた食品容器の孔検出, 2023年電気学会電子・情報・システム部門大会, PS1-7, Aug. 2023.
6.	Yusuke Takata, Ryoji Miyamoto, 石嵜雄一, 荒井健太, 青木仁史, Kenzo Yamaguchi, Masaki Oono and Masami Shishibori : 光技術と深層学習を用いた食品内の異物検知, 日本光学会年次学術講演会, 16pBS4, Nov. 2022.
7.	Masaki Oono, 森内飛希, Masami Shishibori, Masao Fuketa, Kenji Terada and Toshiya Okahisa : One-class SVMに基づく腸蠕動音の自動検出, 第60回日本人工臓器学会大会, Nov. 2022.
8.	HARUKI Hayashi, Masami Shishibori, Masaki Oono, Masao Fuketa, Kenji Terada, 緒方良輔 and Toshiya Okahisa : 胸腹水濾過濃縮時の人工知能を用いた濾過器圧力推移の予測, 第60回日本人工臓器学会大会, Nov. 2022.
9.	REI Nakanishi, Masaki Oono and Masami Shishibori : 深層学習を用いた人物画像に対する3D骨格情報の推定, 令和4年度電気・電子・情報関係学会四国支部連合大会講演論文集, Sep. 2022.
10.	YUTO Nakai, Masaki Oono and Masami Shishibori : 映像内の画像特徴と速度に着目したAI早送り機能, 令和4年度電気・電子・情報関係学会四国支部連合大会講演論文集, Sep. 2022.
11.	TAKUYA Taniguchi, Masaki Oono and Masami Shishibori : 深層学習を用いた異型細胞診のMixupによる精度向上, 令和4年度電気・電子・情報関係学会四国支部連合大会講演論文集, Sep. 2022.
12.	RITSUKI Shinya, Masaki Oono and Masami Shishibori : 差分識別器を用いたGANに基づく歌声分離, 令和4年度電気・電子・情報関係学会四国支部連合大会講演論文集, Sep. 2022.
13.	KAWAHARADA Rie, Masaki Oono and Masami Shishibori : 自己教師あり音高推定手法SPICEにおけるキャリブレーションの最適化, 令和4年度電気・電子・情報関係学会四国支部連合大会講演論文集, Sep. 2022.
14.	Masaki Oono, 森内翔希, Masami Shishibori and Toshiya Okahisa : One-class SVMに基づく教師なし腸蠕動音検出, 令和4年度電気・電子・情報関係学会四国支部連合大会, Sep. 2022.
15.	Masami Shishibori, Masaki Oono, Masao Fuketa, Kenji Terada, 緒方良輔 and Toshiya Okahisa : 胸腹水濾過濃縮専用装置M-CARTへの人工知能応用の可能性, 第59回日本人工臓器学会大会, Nov. 2021.
16.	Shoki Moriuchi, Masaki Oono and Masami Shishibori : 機械学習に基づく腸蠕動音解析システムの開発, 令和3年度電気・電子・情報関係学会四国支部連合大会講演論文集, 17-6, Sep. 2021.
17.	Junnosuke Morioka, Masaki Oono and Masami Shishibori : 伴奏選択モデルに基づく片手用楽譜生成手法, 令和3年度電気・電子・情報関係学会四国支部連合大会講演論文集, 17-5, Sep. 2021.
18.	Zhao Xiaohan, Masaki Oono and Masami Shishibori : 動画配信サービスにおける不適切シーン検出システムの開発, 令和3年度電気・電子・情報関係学会四国支部連合大会講演論文集, 17-4, Sep. 2021.
19.	Kei Shiraishi, Yutaro Maki, Masaki Oono, Akihiro Furube and Masami Shishibori : 金ナノロッド担持ヘマタイトにおける深層学習を用いた領域分割, 第39回固体・表面光化学討論会, Nov. 2020.
20.	多田理香, 竹内彩郁薫, 山田青季, 井形直紀, Masaki Oono, Masami Shishibori, Masao Fuketa, Kenji Terada, Yoshifumi Kida, Tomoyuki Kawaguchi, Yasuhiro Mitsui, Tatsunao Sueuchi, Naoki Muguruma, Tetsuji Takayama, Masahiro Sogabe and Toshiya Okahisa : 睡眠中の腸蠕動音の解析に適した腸音図システムの試作開発., 第58回日本人工臓器学会大会, Nov. 2020.
21.	竹内彩郁薫, 山田青季, 多田理香, 井形直紀, 佐藤翔平, 緒方良輔, 坂東直紀, Yoshiaki Ohnishi, Masaki Oono, Masami Shishibori, Masao Fuketa, Kenji Terada, Shinji Kitamura, Hiroshi Miyamoto, Tetsuji Takayama, Masahiro Sogabe and Toshiya Okahisa : 腹水濾過器洗浄液量の最適化を行うための模擬腹水を用いた評価系の構築., 第58回日本人工臓器学会大会, Nov. 2020.
22.	山田青季, 井形直紀, 竹内彩郁薫, 多田理香, 緒方良輔, 佐藤翔平, 坂東直紀, Yoshiaki Ohnishi, Masaki Oono, Masami Shishibori, Masao Fuketa, Kenji Terada, Kumiko Tanaka, Tetsu Tomonari, Tatsuya Taniguchi, Tetsuji Takayama, Masahiro Sogabe and Toshiya Okahisa : 腹水濾過濃縮再静注法の圧力シート., 第58回日本人工臓器学会大会, Nov. 2020.
23.	Manabu Ishihara, Seiya Takemura, Yasuhisa Kanematsu, Ryoma Morigaki, Nobuaki Yamamoto, Jun Oto, Masaki Oono, Masami Shishibori and Yasushi Takagi : 機械的学習を用いた医療データの解析脳出血症例の検討, 第79回日本脳神経外科学会学術総会, Oct. 2020.
24.	Ryota Nishio, Masaki Oono and Masami Shishibori : A generation method of 3D face model from 2D face image using the deep learning model, 令和2年度電気・電子・情報関係学会四国支部連合大会講演論文集, 13-15, Sep. 2020.
25.	Harumi Kadota, Masaki Oono and Masami Shishibori : Automatic decoration of face images using deep learning, 令和2年度電気・電子・情報関係学会四国支部連合大会講演論文集, 13-16, Sep. 2020.
26.	Hiroki Inoue, Masaki Oono and Masami Shishibori : Chorus section detection based on singing voice, 令和2年度電気・電子・情報関係学会四国支部連合大会講演論文集, 17-3, Sep. 2020.
27.	Hiroshi Akiwa, Masaki Oono and Masami Shishibori : Music summarization focused on singing voice and repeated section, 令和2年度電気・電子・情報関係学会四国支部連合大会講演論文集, 17-2, Sep. 2020.
28.	Takeaki Washida, Masaki Oono, Takeshi Oya, Koichi Tsuneyama and Masami Shishibori : 深層学習を用いた尿細胞診断の自動化手法, 第19回情報科学技術フォーラム講演論文集(FIT2020)第2分冊, 273-274, Sep. 2020.
29.	Shun Sakoda, Masaki Oono and Masami Shishibori : 卓球動画における深層学習を用いたスローモーションシーン検出手法, 第19回情報科学技術フォーラム講演論文集(FIT2020)第3分冊, 101-102, Sep. 2020.
30.	Masaki Oono and Masami Shishibori : A Method of Generating Left-hand Piano Score Based on Hidden Markov Model, 情報処理学会情報科学技術フォーラム, Sep. 2019.
31.	笠原尚弥, Masaki Oono and Masami Shishibori : 顔領域に着目した漫画の著者推定に関する研究, 情報処理学会情報科学技術フォーラム, H-028, Sep. 2019.
32.	迫田峻, Masaki Oono and Masami Shishibori : ゴール領域に着目したバスケットボール番組のシュートシーン検出に関する研究, 情報処理学会情報科学技術フォーラム, H-024, Sep. 2019.
33.	鷲田武晃, Masaki Oono and Masami Shishibori : 物体領域に着目した画像分類に関する研究, 情報処理学会情報科学技術フォーラム, H-008, Sep. 2019.
34.	Masaki Oono, Toshiki Katoh and Masami Shishibori : A Method of Generating One-hand Piano Score for Persons with Disablilities of Fingers, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 216, Sep. 2018.
35.	Shoma Takamatsu, Masaki Oono and Masami Shishibori : 手書きイラストを対象とした顔パーツ領域抽出手法に関する研究, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 216, Sep. 2017.
36.	Kuniyuki Funasaka, Masaki Oono and Masami Shishibori : HMMに基づくドラムフィルインの自動生成手法に関する研究, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 215, Sep. 2017.
37.	Shogo Mori, Masaki Oono and Masami Shishibori : 音域に着目したサビ区間検出手法に関する研究, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 214, Sep. 2017.
38.	中西雅哉, Masaki Oono and Masami Shishibori : 特定物体認識におけるSIFT特徴点マッチング手法の改善, 情報処理学会第79回全国大会講演論文集, Vol.1, 495, Mar. 2017.
39.	向原啓悟, Masaki Oono and Masami Shishibori : クロマベクトルに基づくインストゥルメンタル楽曲検索手法に関する研究, 平成28年度電気関係学会四国支部連合大会講演論文集, 232, Sep. 2016.
40.	中西雅哉, Masaki Oono and Masami Shishibori : 局所特徴量の類似性・出現位置を考慮した特定物体認識手法に関する研究, 平成28年度電気関係学会四国支部連合大会講演論文集, 177, Sep. 2016.
41.	上野総司郎, Masaki Oono and Masami Shishibori : DPマッチングに基づく時間伸縮を考慮した音響指紋照合手法に関する研究, 平成28年度電気関係学会四国支部連合大会講演論文集, 233, Sep. 2016.
42.	大野竜河, Masaki Oono and Masami Shishibori : モーションセンサを用いたプレゼンテーション支援システムの開発, 平成28年度電気関係学会四国支部連合大会講演論文集, 241, Sep. 2016.
43.	春江諒佑, Masaki Oono and Masami Shishibori : 繰り返し構造に基づくライブ演奏楽曲の検索手法に関する研究, 情報処理学会全国大会講演論文集, 495-496, Mar. 2016.
44.	明石雄太, Masaki Oono and Masami Shishibori : 要約レベルを考慮した音楽要約システムに関する研究, 情報処理学会全国大会講演論文集, 503-504, Mar. 2016.
45.	山口大範, Masaki Oono and Masami Shishibori : Character modifying method for penmanship support systems, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 240, Sep. 2015.
46.	野村佳輝, Masaki Oono and Masami Shishibori : A method of specific object search considering peripheral colors of feature point, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 202, Sep. 2015.
47.	大関陽裕, Masaki Oono and Masami Shishibori : 局所特徴量の出現位置分布に基づく特定物体認識手法, 情報処理学会全国大会講演論文集, 549-550, Mar. 2015.
48.	東秀賢, Masaki Oono and Masami Shishibori : 手のぶれを考慮した手洗い検査システムの改善, 情報処理学会全国大会講演論文集, 241-242, Mar. 2015.
49.	田村晴康, Masaki Oono and Masami Shishibori : An emotion control method for music based on multiple regression, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 291, Sep. 2014.
50.	大岡史知, Masaki Oono and Masami Shishibori : An Efficient Method for Detecting Chorus Sections Based on Near the End of Music, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 290, Sep. 2014.
51.	東秀賢, Masaki Oono and Masami Shishibori : カメラ映像を用いた手洗い検査システムの開発, 情報処理学会全国大会講演論文集, 265-266, Mar. 2014.
52.	中西康公, Masaki Oono and Masami Shishibori : 局所特徴量に基づくネジ種の自動識別手法に関する研究, 情報処理学会全国大会講演論文集, 75-76, Mar. 2014.
53.	大関陽裕, Masaki Oono and Masami Shishibori : 小型自律飛行ロボットを用いた案内システムの開発, 情報処理学会全国大会講演論文集, 181-182, Mar. 2014.
54.	大滝尚輝, Masaki Oono and Masami Shishibori : An assist system for presentation using Kinect, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 344, Sep. 2013.
55.	河原健太, Masami Shishibori and Masaki Oono : A Method to Detect similar playlist based on Bag of Feartures, Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 315, Sep. 2013.
56.	Masaki Oono, 岡村亮一, Masami Shishibori and 沼尾雅之 : 個人の嗜好を考慮したメドレー曲自動生成手法, IPSJ SIG Technical Report, Vol.100, No.35, 1-6, Aug. 2013.
57.	篠原透, Masaki Oono and 沼尾雅之 : 作曲支援のためのマイニングによる和声進行提示システムの提案, 情報処理学会全国大会講演論文集, 285-286, Mar. 2013.
58.	Masaki Oono : 社会ネットワークの成長を考慮したインフルエンスノード抽出手法, 電子情報通信学会技術研究報告, Vol.112, No.94, 33-37, Jun. 2012.
59.	Masaki Oono : 社会ネットワークの時間変化を考慮した情報拡散モデルの検討, 電子情報通信学会データ工学研究会, Dec. 2011.
60.	Masaki Oono and 小川卓人 : 歌詞の構造に基づく楽曲の繰り返し構造推定, 第9回情報科学技術フォーラム, Sep. 2010.
61.	Masaki Oono, Kazuhiro Morita, Masao Fuketa and Jun-ichi Aoe : ダブル配列による自然言語辞書の高速更新法, 言語処理学会第11回年次大会, 745-748, Mar. 2005.
62.	Susumu Yata, Masaki Oono, Kazuhiro Morita, Masao Fuketa and Jun-ichi Aoe : ダブル配列構造による自然言語辞書の記憶量圧縮法, 言語処理学会第11回年次大会, 309-312, Mar. 2005.

Grants-in-Aid for Scientific Research (KAKEN Grants Database @ NII.ac.jp)

雑音環境における解釈可能な腸蠕動音自動検出システムの構築 (Project/Area Number: 23K11896 )
実技学習支援を目的とした深層学習による3Dボディ生成システムの開発 (Project/Area Number: 21K12175 )
腹部聴診音のコンピューター解析による過敏性腸症候群の病態評価システムの構築 (Project/Area Number: 19K12824 )
A method of generating one-hand piano score for disabled persons of the hand and fingers (Project/Area Number: 19K12248 )
Development of a system to support playing musical instruments using augmented reality technology (Project/Area Number: 18K11573 )
Development of a hand-washing support system by using video processing technologies (Project/Area Number: 15K00482 )
Search by Researcher Number (90433739)

Associate Professor : Oono, Masaki

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Grants-in-Aid for Scientific Research (KAKEN Grants Database @ NII.ac.jp)