https://nova.newcastle.edu.au/vital/access/ /manager/Index en-au 5 Using deep learning to assess eating behaviours with wrist-worn inertial sensors https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:40792 Wed 06 Mar 2024 15:18:41 AEDT ]]> Using deep learning to detect food intake behavior from video https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:38695 Wed 03 Apr 2024 14:23:13 AEDT ]]> Learning deep representations for video-based intake gesture detection https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:38698 Thu 13 Jan 2022 14:48:32 AEDT ]]> Single-Stage Intake Gesture Detection Using CTC Loss and Extended Prefix Beam Search https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45778 Sat 05 Nov 2022 12:35:18 AEDT ]]> Deep learning for intake gesture detection from wrist-worn inertial sensors: the effects of data preprocessing, sensor modalities, and sensor positions https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39083 1=.778 ). As for data preprocessing, results show that applying a consecutive combination of mirroring, removing gravity effect, and standardization was beneficial for model performance, while smoothing had adverse effects. We further investigate the effectiveness of using different combinations of sensor modalities (i.e., accelerometer and/or gyroscope) and sensor positions (i.e., dominant intake hand and/or non-dominant intake hand).]]> Fri 06 May 2022 15:21:38 AEST ]]>