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计算机视觉和深度转移学习用于自动测量器读取检测

Hitesh Ninama1,2, Jagdish Raikwal1, Ananda Ravuri3

  • 1Institute of Engineering and Technology, Devi Ahilya University, Indore, M.P., 452001, India.

Scientific reports
|October 3, 2024
PubMed
概括

本研究介绍了一种人工智能系统,用于使用深度学习进行自动模拟仪表读取. DenseNet 169实现了卓越的精度和概括性,用于准确的标尺解释.

关键词:
计算机视觉 计算机视觉 计算机视觉深度学习是一种深度学习.密集网络 169 密集网络测量仪检测检测仪表检测仪表检测仪表检测仪表检测仪表检测仪表检测仪表检测仪表发明网络 V3 发明网络 V3在VGG19中,VGG19在VGG19中.

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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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