Výsledky vyhledávání

Akademický článek

Adaptive weighted multi-view subspace clustering method for recognizing urban functions from multi-source social sensing data

Autor: Qiliang Liu, Zexin Lu, Weihua Huan, Chong Fan

Publikováno v: Geo-spatial Information Science, Pp 1-25 (2024)

Multi-source social sensing data provide new opportunities to identify urban functions from the perspective of human activity. The information embedded in multi-source data typically needs to be fused to obtain a comprehensive view of urban functions

Externí odkaz: https://doaj.org/article/24b047d5a68847cb8efdf6729495ed8f

Zobrazit plný text záznamu

Akademický článek

A Multi-Modal Entity Alignment Method with Inter-Modal Enhancement

Autor: Song Yuan, Zexin Lu, Qiyuan Li, Jinguang Gu

Publikováno v: Big Data and Cognitive Computing, Vol 7, Iss 2, p 77 (2023)

Due to inter-modal effects hidden in multi-modalities and the impact of weak modalities on multi-modal entity alignment, a Multi-modal Entity Alignment Method with Inter-modal Enhancement (MEAIE) is proposed. This method introduces a unique modality

Externí odkaz: https://doaj.org/article/938db70fc9014f8385a8312cd64fc4c3

Zobrazit plný text záznamu

Akademický článek

Power Allocation for Multiple Transmitter-Receiver Pairs Under Frequency-Selective Fading Based on Convolutional Neural Network

Autor: Mingjun Dai, Qingwen Huang, Zexin Lu, Bin Chen, Hui Wang, Xue Qin

Publikováno v: IEEE Access, Vol 8, Pp 31018-31025 (2020)

For multiple transmitter-receiver pairs communication in a frequency-selective environment, typical power allocation method is the Iterative-Waterfilling (IW) algorithm. Main drawback of IW is its poor convergence performance, including low convergen

Externí odkaz: https://doaj.org/article/97c4682b5c8d432c816f3f3c3f9531b2

Zobrazit plný text záznamu

Akademický článek

SSDC-DenseNet: A Cost-Effective End-to-End Spectral-Spatial Dual-Channel Dense Network for Hyperspectral Image Classification

Autor: Yutong Bai, Qifan Zhang, Zexin Lu, Yi Zhang

Publikováno v: IEEE Access, Vol 7, Pp 84876-84889 (2019)

In recent years, various deep learning-based methods have been applied in hyperspectral image (HSI) classification. Among them, spectral-spatial approaches have demonstrated their power to yield high accuracies. However, these methods tend to be comp

Externí odkaz: https://doaj.org/article/c307e2bd2ba9406994df6a176816ac18

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání