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.