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of 288
pro vyhledávání: '"Ruan, Xiang"'
Image-text matching remains a challenging task due to heterogeneous semantic diversity across modalities and insufficient distance separability within triplets. Different from previous approaches focusing on enhancing multi-modal representations or e
Externí odkaz:
http://arxiv.org/abs/2404.18114
Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching. Generally, recent approaches first employ a cross-modal attention unit to capture latent region-word interactions, and then integr
Externí odkaz:
http://arxiv.org/abs/2303.13371
With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' temperature information. However, the lack of paired training samples i
Externí odkaz:
http://arxiv.org/abs/2204.04120
Correlation has a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion method that considers the similarity between the template and the search region. However, the cor
Externí odkaz:
http://arxiv.org/abs/2203.13533
Autor:
Gao, Xin, Yan, Di, Zhang, Ya, Ruan, Xiang, Kang, Tingyu, Wang, Ruotong, Zheng, Qi, Chen, Siju, Zhai, Jinxia
Publikováno v:
In Nurse Education in Practice March 2024 76
Existing CNNs-Based RGB-D salient object detection (SOD) networks are all required to be pretrained on the ImageNet to learn the hierarchy features which helps provide a good initialization. However, the collection and annotation of large-scale datas
Externí odkaz:
http://arxiv.org/abs/2101.12482
Publikováno v:
In Pattern Recognition Letters April 2023 168:10-16
Fully convolutional neural networks (FCNs) have shown outstanding performance in many dense labeling problems. One key pillar of these successes is mining relevant information from features in convolutional layers. However, how to better aggregate mu
Externí odkaz:
http://arxiv.org/abs/1708.02001
Autor:
Lei, Xiang-Cui, Heng, Yue-Kun, Qian, Sen, Xia, Jing-Kai, Liu, Shu-Lin, Wu, Zhi, Yan, Bao-Jun, Xu, Mei-Hang, Wang, Zheng, Li, Xiao-Nan, Ruan, Xiang-Dong, Wang, Xiao-Zhuang, Yang, Yu-Zhen, Wang, Wen-Wen, Fang, Can, Luo, Feng-Jiao, Liang, Jing-Jing, Yang, Lu-Ping, Yang, Biao
The neutrino detector of the Jiangmen Underground Neutrino Observatory (JUNO) is designed to use 20 kilotons of liquid scintillator and approximately 16,000 20-inch photomultipliers (PMTs).One of the options is to use the 20-inch R12860 PMT with high
Externí odkaz:
http://arxiv.org/abs/1504.03174
Publikováno v:
Journal of Asian Architecture & Building Engineering; Jul2024, Vol. 23 Issue 4, p1371-1380, 10p