Tomohiro Yamada, Naoto Hiramatsu, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto, Logical Anomaly Detection based on Relative Similarity Analysis of Region Segments, International Workshop on Advanced Image Technology 2026 (IWAIT2026), vol.14072, 140721R, 2026/01/12.
Naoki Murakami, Naoto Hiramatsu, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto, Subspace-Based Embedded Feature Reduction for Fast Anomaly Detection, In Scandinavian Conference on Image Analysis 2025 (SCIA2025), vol.15726, pp.210-223, Reykjavik, Iceland, 2025/06/23.
Naoki Murakami, Naoto Hiramatsu, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto, DC-PaDiM: Fast Anomaly Detection based on Effective Feature Dimension-Compression, In 2024 Twelfth International Symposium on Computing and Networking (CANDAR), IEEE, pp. 190-195, Okinawa, Japan, 2024/11/27.
Hiroki Kobayashi, Naoki Murakami, Naoto Hiramatsu, Takahiro Suzuki, Manabu Hashimoto, Anomaly Detection Based on Semi-Formula Driven Pre-training Dataset to Represent Subtle Difference and Anomaly Score, The 35th British Machine Vision Conference (BMVC2024), pp.1-12, Scottish Event Campus, Glasgow, UK, 2024/11/26.
Naoto Hiramatsu, Naoki Murakami, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto, DoG-PaDiM: Anomaly Detection Based on Bandpass Filtering for Arbitrary Size Defect Extraction, IEEE 20th International Conference on Automation Science and Engineering (CASE2024), pp.2850-2855, 2024/8/31.
Naoki Murakami, Naoto Hiramatsu, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto, A proposal of anomaly detection method based on natural data augmentation in the Eigenspace, Journal of WSCG, 2024, vol. 32, no. 1-2, p. 91-100, 2024/6/4.
国内シンポジウム:28件(内,筆頭9件)
小原那南斗,村上尚生,平松直人,小林大起 ,秋月秀一 ,橋本学,画像内領域の構成要素内および要素間特徴の統合評価に基づくMVTec Juice bottleカテゴリのための論理的異常検知手法の提案,動的画像処理実利用化ワークショップ2026(DIA2026),IS1-29,pp.187-192,高知工科大学永国寺キャンパス,2026/03/03.