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INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile ...
The dataset used in this paper is a Conv1D equipped ASR model deployed on mobile devices. -
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
ShuffleNet is an extremely efficient convolutional neural network for mobile devices. -
Temporal Convolution for Real-time Keyword Spotting on Mobile Devices
Keyword spotting (KWS) plays a critical role in enabling speech-based user interactions on smart devices. Recent developments in the field of deep learning have led to wide... -
Sussex-Huawei Locomotion (SHL) dataset
A large dataset for multimodal analytics with mobile devices. -
Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Bas...
Human Activity Recognition on mobile devices using a realistic heterogeneous setting with four different public datasets.