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密集的D2C-Net:用于显示器到摄像头通信的密集连接网络
Optics express
|September 15, 2023
概括
这项研究介绍了Dense D2C-Net,这是一种新的显示到摄像头 (D2C) 方法,使用深 convolutional 神经网络 (DCNNs) 来嵌入图像中的数据. 该方案在现实世界测试中实现了卓越的性能,保持了视觉质量和数据完整性.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 信息技术 信息技术 信息技术
背景情况:
- 显示到摄像头 (D2C) 通信可通过视觉内容进行数据传输.
- 现有的基于DCNN的D2C方案在视觉质量和稳定性方面面临挑战.
研究的目的:
- 介绍Dense D2C-Net,这是一个基于DCNN的新方案,可以通过视觉内容轻松嵌入和提取数据.
- 提高D2C通信中的数据完整性和视觉质量.
主要方法:
- 开发了Dense D2C-Net,这是一个DCNN架构,具有层间连接和特征重复使用的编码.
- 利用Y通道嵌入二进制数据,因为它的稳定性.
- 集成的混合层和噪声层,以改善数据隐藏和减轻频道扭曲.
- 在解码器上使用2D卷积层来提取数据.
主要成果:
- 与传统的基于DCNN的D2C方案相比,Dense D2C-Net的表现优越.
- 通过各种参数验证了有效性:传输距离,捕捉角度,显示亮度和摄像头分辨率.
- 保持了封面图像与嵌入数据的高视觉质量.
结论:
- 密集的D2C-Net提供了一个强大而高效的解决方案,用于显示器与摄像头之间的通信.
- 拟议的方案在通过视觉内容嵌入和提取数据方面取得了重大进展.
- 对于使用智能手机摄像头和数字显示器的现实应用程序是有效的.
相关概念视频
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In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
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