Výsledky vyhledávání - "Mao, Yingchi"

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ICST-DNET: An Interpretable Causal Spatio-Temporal Diffusion Network for Traffic Speed Prediction

Autor: Rong, Yi, Mao, Yingchi, Liu, Yinqiu, Chen, Ling, He, Xiaoming, Niyato, Dusit

Traffic speed prediction is significant for intelligent navigation and congestion alleviation. However, making accurate predictions is challenging due to three factors: 1) traffic diffusion, i.e., the spatial and temporal causality existing between t

Externí odkaz: http://arxiv.org/abs/2404.13853

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DD-GCN: Directed Diffusion Graph Convolutional Network for Skeleton-based Human Action Recognition

Autor: Li, Chang, Huang, Qian, Mao, Yingchi

Graph Convolutional Networks (GCNs) have been widely used in skeleton-based human action recognition. In GCN-based methods, the spatio-temporal graph is fundamental for capturing motion patterns. However, existing approaches ignore the physical depen

Externí odkaz: http://arxiv.org/abs/2308.12501

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Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction

Autor: Pranolo, Andri, Mao, Yingchi, Wibawa, Aji Prasetya, Utama, Agung Bella Putra, Dwiyanto, Felix Andika

Publikováno v: Knowledge Engineering and Data Science, 2022, Vol 5 No 1, pp: 53-66

Deep learning is a machine learning approach that produces excellent performance in various applications, including natural language processing, image identification, and forecasting. Deep learning network performance depends on the hyperparameter se

Externí odkaz: http://arxiv.org/abs/2306.07296

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