Active Online Learning Architecture for Multimodal Sensor-based ADL Recognition. - Nobuyuki Oishi; Masayuki Numao (AAAI Spring Symposia, 2018)

Measuring Functional Independence of an Aged Person with a Combination of Machine Learning and Logical Reasoning. - Nobuyuki Oishi; Masayuki Numao (AAAI Spring Symposium: Interpretable AI for Well-being, 2019)

Detecting Freezing of Gait with Earables Trained from VR Motion Capture Data. - Nobuyuki Oishi; Benedetta Heimler; Lloyd Pellatt; Meir Plotnik; Daniel Roggen (ISWC, 2021)

Hierarchical Feature Recovery for Robust Human Activity Recognition in Body Sensor Networks. - Nobuyuki Oishi; Paula Lago; Phil Birch; Daniel Roggen (UbiComp/ISWC Adjunct, 2022)

Investigating the Effect of Orientation Variability in Deep Learning-based Human Activity Recognition. - Azhar Ali Khaked; Nobuyuki Oishi; Daniel Roggen; Paula Lago (UbiComp/ISWC Adjunct, 2023)

Learning Using Privileged Information for Wearable-based Human Activity Recognition. - Nobuyuki Oishi; Daniel Roggen; Philip Birch; Paula Lago (PerCom Workshops, 2023)

Keep the Key Part: Exploring Drone-Captured Digital Elevation Model Data Augmentation for Deep Learning-based Crop Height Estimation. - Jinjin Wang; Nobuyuki Oishi; Renhui Ying; Guiyi Wei; Phil Birch; Bao Kha Nguyen (VCIP, 2024)

WIMUSim: simulating realistic variabilities in wearable IMUs for human activity recognition. - Nobuyuki Oishi; Phil Birch; Daniel Roggen; Paula Lago (Frontiers Comput. Sci., 2025)

ETTrack: enhanced temporal motion predictor for multi-object tracking. - Xudong Han; Nobuyuki Oishi; Yueying Tian; Elif Ucurum; Rupert C. D. Young; Chris R. Chatwin; Philip Birch (Appl. Intell., 2025)

In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models against Variability. - Azhar Ali Khaked; Nobuyuki Oishi; Daniel Roggen; Paula Lago (CoRR, 2025)

Physically Plausible Data Augmentations for Wearable IMU-based Human Activity Recognition Using Physics Simulation. - Nobuyuki Oishi; Philip Birch; Daniel Roggen; Paula Lago (CoRR, 2025)