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A Survey on Approaches of Motion Mode Recognition Using Sensors.

, , , and . IEEE Trans. Intell. Transp. Syst., 18 (7): 1662-1686 (2017)

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A Survey on Approaches of Motion Mode Recognition Using Sensors., , , and . IEEE Trans. Intell. Transp. Syst., 18 (7): 1662-1686 (2017)Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data., , , , , , , , , and . CoRR, (2023)Accelerating Training using Tensor Decomposition., , , , and . CoRR, (2019)One-Shot Layer-Wise Accuracy Approximation For Layer Pruning., , , , and . ICIP, page 2940-2944. IEEE, (2020)CHAI: Clustered Head Attention for Efficient LLM Inference., , , , , , , and . CoRR, (2024)SIEVE: Multimodal Dataset Pruning Using Image Captioning Models., , , , , , and . CoRR, (2023)Motion Mode Recognition for Indoor Pedestrian Navigation Using Portable Devices., , , and . IEEE Trans. Instrum. Meas., 65 (1): 208-221 (2016)DeepShift: Towards Multiplication-Less Neural Networks., , , , and . CoRR, (2019)OLLA: Decreasing the Memory Usage of Neural Networks by Optimizing the Lifetime and Location of Arrays., , , and . CoRR, (2022)Work-in-Progress: MLGOPerf: An ML Guided Inliner to Optimize Performance., , , , , , and . CASES, page 3-4. IEEE, (2022)