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Towards multimodal deep learning for activity recognition on mobile devices.

, , , , , and . UbiComp Adjunct, page 185-188. ACM, (2016)

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Smart at what cost?: characterising mobile deep neural networks in the wild., , , , , and . Internet Measurement Conference, page 658-672. ACM, (2021)vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer., , , , , and . CoRR, (2023)Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions., , and . CoRR, (2021)AgreementLearning: An End-to-End Framework for Learning with Multiple Annotators without Groundtruth., , , , , , and . CoRR, (2021)Zero-Cost Operation Scoring in Differentiable Architecture Search., , , , , and . AAAI, page 10453-10463. AAAI Press, (2023)EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions., , , , , , , , , and . FG, page 849-856. IEEE, (2020)DXTK: Enabling Resource-efficient Deep Learning on Mobile and Embedded Devices with the DeepX Toolkit., , , , and . MobiCASE, page 98-107. ACM / ICST, (2016)A Vision for Adaptive and Generalizable Audio-Sensing Systems., , , and . SocialSens@CPSIoTWeek, page 43. ACM, (2019)An Empirical study of Binary Neural Networks' Optimisation., , , and . ICLR (Poster), OpenReview.net, (2019)Mic2Mic: using cycle-consistent generative adversarial networks to overcome microphone variability in speech systems., , , , and . IPSN, page 169-180. ACM, (2019)