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Authors = Xiaosuo Wu

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15 pages, 4178 KiB  
Article
High-Resolution Remote Sensing Image Change Detection Based on Cross-Mixing Attention Network
by Chaoyang Wu, Le Yang, Cunge Guo and Xiaosuo Wu
Electronics 2024, 13(3), 630; https://doi.org/10.3390/electronics13030630 - 2 Feb 2024
Viewed by 2030
Abstract
With the powerful discriminative capabilities of convolutional neural networks, change detection has achieved significant success. However, current methods either ignore the spatiotemporal dependencies between dual-temporal images or suffer from decreased accuracy due to registration errors. Addressing these challenges, this paper proposes a method [...] Read more.
With the powerful discriminative capabilities of convolutional neural networks, change detection has achieved significant success. However, current methods either ignore the spatiotemporal dependencies between dual-temporal images or suffer from decreased accuracy due to registration errors. Addressing these challenges, this paper proposes a method for remote sensing image change detection based on the cross-mixing attention network. To minimize the impact of registration errors on change detection results, a feature alignment module (FAM) is specifically developed in this study. The FAM performs spatial transformations on dual-temporal feature maps, achieving the precise spatial alignment of feature pairs and reducing false positive rates in change detection. Additionally, to fully exploit the spatiotemporal relationships between dual-temporal images, a cross-mixing attention module (CMAM) is utilized to extract global channel information, enhancing feature selection capabilities. Furthermore, attentional maps are created to guide the up-sampling process, optimizing feature information. Comprehensive experiments conducted on the LEVIR-CD and SYSU-CD change detection datasets demonstrate that the proposed model achieves F1 scores of 91.06% and 81.88%, respectively, outperforming other comparative models. In conclusion, the proposed model maintains good performance on two datasets and, thus, has good applicability in various change detection tasks. Full article
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15 pages, 3084 KiB  
Article
Design and Optimization of Asymmetric Grating Assisted Slot Microring
by Chunjuan Liu, Jiawei Wang, Xiaosuo Wu, Xiaoli Sun, Ze Qiao, Yuqiang Xin and Jiangfeng Zhang
Photonics 2022, 9(12), 988; https://doi.org/10.3390/photonics9120988 - 15 Dec 2022
Cited by 2 | Viewed by 3211
Abstract
In this paper, a slot microring with an asymmetric grating structure is proposed. Through the coupling between the grating and the slot microring, a high free spectral range or EIT-like effects with a high quality factor can be achieved in the same device. [...] Read more.
In this paper, a slot microring with an asymmetric grating structure is proposed. Through the coupling between the grating and the slot microring, a high free spectral range or EIT-like effects with a high quality factor can be achieved in the same device. The grating is designed as an asymmetric structure to realize the modulation of the optical signal and the control of the resonance peak by changing the grid number, and the effect of different grating periods on the output spectrum is explored. The results show that changing the grating on slot sidewalls can increase or decrease the number of resonant peaks. By selecting a specific period of the gratings on both sides of the slot, the distance between adjacent resonance peaks can be increased to achieve modulation of the free spectral range. In this paper, depending on the grating period, we obtain a quality factor of 5016 and an FSR of 137 nm, or a quality factor of 10,730 and an FSR of 92 nm. The refractive index sensing simulation is carried out for one of the periods, which can achieve a sensitivity of 370 nm/RIU. Therefore, the proposed new structure has certain advantages in different sensing applications. Full article
(This article belongs to the Special Issue Integrated Waveguide-Based Photonic Devices)
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