町田 文雄(マチダ フミオ)
- 会議発表等
- How Data Diversification Benefits the Reliability of Three-version Image Classification Systems
Takahashi Mitsuho; Machida Fumio; Wen Qiang
The 27th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC)/2022-12 - Performance Bottleneck Analysis of Drone Computation Offloading to a Shared Fog Node
Zhang Qingyang; Machida Fumio; Andrade Ermeson
The 12th IEEE International Workshop on Software Certification (WoSoCer)/2022-10 - Analysis of Software Aging in a Blockchain Platform
Dias Douglas; Andrade Ermeson; Machida Fumio
The 14th International Workshop on Software Aging and Rejuvenation (WoSAR)/2022-10 - Availability Analysis of a Drone System with Proactive Offloading for Software Life-extension
Watanabe Kengo; Machida Fumio
IEEE Conference on Omni-layer INtelligent Systems (COINS)/2022-08 - Reliability Models and Analysis for Triple-model with Triple-input Machine Learning Systems
Wen Qiang; Machida Fumio
IEEE Conference on Dependable and Secure Computing (DSC)/2022-05 - Toward performance and reliability assurance of UAV-based ecological monitoring systems
張清洋; 町田 文雄
第20回ディペンダブルシステムワークショップ (DSW 2022)/2022-12-15 - 2入力機械学習システムの信頼性と性能評価
脇上和也; 町田 文雄
第20回ディペンダブルシステムワークショップ (DSW 2022)/2022-12-15 - Nバージョン機械学習モデルによるシステム高信頼化のための入力データ多様化
高橋満帆; 町田 文雄
ディペンダブルシステムワークショップ（DSW 2021）/2021-12-16--2021-12-17 - 画像処理タスクのオフローディングによるドローンシステムのソフトウェア延命
渡邉賢吾; 町田 文雄
ディペンダブルシステムワークショップ（DSW 2021）/2021-12-16--2021-12-17 - Nバージョン機械学習分類システムによる分類結果の正確性と安全性評価
町田 文雄
日本信頼性学会 第30回春季信頼性シンポジウム/2022-05 - Availability Modeling for Drone Image Processing Systems with Adaptive Offloading
Machida Fumio; Andrade Ermeson
IEEE Pacific Rim International Symposium on Dependable Computing (PRDC)/2021-12-01--2021-12-04 - Performance analysis of machine learning-based systems for detecting deforestation
Araujo Michel de; Andrade Ermeson; Machida Fumio
Brazilian Symposium on Computing Systems Engineering (SBESC)/2021-11-21--2021-11-24 - Memory Degradation Analysis in Private and Public Cloud Environments
Andrade Ermeson; Machida Fumio; Pietrantuono Roberto; Cot...
International Workshop on Software Aging and Rejuvenation/2021-10-25 - Failure threshold setting for Wiener-process-based remaining useful life estimation
Liu Xingzhi; Machida Fumio
IEEE Global Reliability & Prognostics and Health Management Conference/2021-10-15--2021-10-17 - A Queueing Analysis of Multi-model Multi-input Machine Learning Systems
Tuan Phung-Duc; Yuta Makino; Fumio Machida
The 4th DSN Workshop on Dependable and Secure Machine Learning (DSN-DSML'21)/2021-06-21--2021-06-21 - マルコフ連鎖を用いた多モデル多入力型機械学習システムの性能評価
巻野 侑大; Tuan Phung-Duc; 町田 文雄
第37回（2020年度）待ち行列シンポジウム「確率モデルとその応用」/2021-01-25--2021-01-27 - A Robustness Evaluation of Concept Drift Detectors against Unreliable Data Streams
Machida Fumio; Wang Sixiang
IEEE 7th World Forum on the Internet of Things/2021-06 - PA-offload: Performability-aware Adaptive Fog Offloading for Drone Image Processing
Machida Fumio; Andrade Ermeson
IEEE International Conference on Fog and Edge Computing (ICFEC2021)/2021-05 - Software aging in image classification systems on cloud and edge
Machida Fumio; Andrade Ermeson; Pietrantuono Roberto; Cot...
International Workshop on Software Aging and Rejuvenation (WoSAR)/2020-10 - Markov chains and Petri nets for software rejuvenation systems
Machida Fumio; Paulo R. M. Maciel
International Workshop on Software Aging and Rejuvenation (WoSAR)/2020-10 - 多様な分類器を用いた機械学習応用システムの信頼性
町田 文雄
日本OR学会「4部合同研究会 ～確率モデルの新展開～」/2019-10-19 - Nバージョンモデルによる機械学習応用システムの高信頼化
町田 文雄
第17回 ディペンダブルシステムワークショップ（DSW2019）/2019-12-06 - N-version machine learning models for safety critical systems
Machida Fumio
DSN Workshop on Dependable and Secure Machine Learning/2019-06 - Analysis of software aging impacts on plant anomaly detection with edge computing
Machida Fumio; Andrade Ermeson
Int’l Works. on Software Aging and Rejuvenation/2019-10 - On the diversity of machine learning models for system reliability
Machida Fumio
IEEE Pacific Rim Int'l Symp. on Dependable Computing (PRDC)/2019-12-01--2019-12-03 - さらに表示...
- How Data Diversification Benefits the Reliability of Three-version Image Classification Systems