edge patch

简明释义

边覆条

英英释义

例句

1.We need to apply an edge patch to prevent further wear on the edges of the carpet.

我们需要应用一个边缘补丁以防止地毯边缘进一步磨损。

2.The designer added an edge patch to enhance the visual appeal of the garment.

设计师在服装上添加了一个边缘补丁以增强视觉吸引力。

3.In software development, an edge patch can fix vulnerabilities in the system.

在软件开发中，边缘补丁可以修复系统中的漏洞。

4.The game developers released an edge patch to balance gameplay and fix bugs.

游戏开发者发布了一个边缘补丁来平衡游戏性并修复漏洞。

5.You can use an edge patch to cover up any damage on the edges of the picture frame.

你可以使用一个边缘补丁来遮盖相框边缘的任何损坏。

作文

In the world of computer graphics and image processing, the term edge patch refers to a specific area or section of an image that is located near the boundary or edge of the object within the image. Understanding the concept of edge patch is crucial for various applications, including image segmentation, object recognition, and even in enhancing the quality of images. An edge patch typically contains significant information about the transition between different regions of an image, making it a focal point for algorithms that aim to detect edges or boundaries. For instance, when an image is processed to identify objects, the edge patch plays a vital role. It helps in determining where one object ends and another begins. This is particularly important in complex images where multiple objects overlap or are closely positioned. By analyzing the edge patch, algorithms can effectively distinguish between these objects, leading to more accurate results in tasks such as autonomous driving, facial recognition, and medical imaging.Moreover, the study of edge patches extends beyond just detection. It also involves the enhancement of images. In image editing software, users often apply filters that focus on the edge patches to sharpen or soften the edges of objects. This process improves the visual aesthetics of images, making them more appealing to viewers. For example, photographers might enhance the edge patches of a landscape photo to make the trees stand out against the sky, creating a more dramatic effect.In addition to practical applications, the concept of edge patches can also be related to theoretical aspects of image analysis. Researchers study how different algorithms handle edge patches to improve performance and accuracy. By understanding the characteristics of edge patches, they can develop better techniques for image processing that minimize errors and enhance the overall quality of the output. This research is vital in fields such as artificial intelligence, where machines learn to interpret visual data similarly to humans.Furthermore, the importance of edge patches can be seen in the realm of machine learning. Convolutional neural networks (CNNs), which are widely used in image classification tasks, rely heavily on identifying edge patches. These networks learn to recognize patterns and features in images by focusing on the edges first, which serve as primary indicators of shapes and forms. The ability of CNNs to accurately classify images often depends on their proficiency in detecting and interpreting edge patches.In conclusion, the term edge patch encompasses a critical aspect of image processing and analysis. Whether in the context of enhancing images, recognizing objects, or developing machine learning algorithms, understanding edge patches is fundamental. As technology continues to evolve, the significance of edge patches will only grow, influencing how we interact with and interpret visual information in our increasingly digital world.

在计算机图形学和图像处理领域，术语edge patch指的是图像中位于物体边界或边缘附近的特定区域或部分。理解edge patch的概念对于各种应用至关重要，包括图像分割、物体识别，甚至提高图像质量。edge patch通常包含有关图像不同区域之间过渡的重要信息，使其成为旨在检测边缘或边界的算法的重点。例如，当处理图像以识别物体时，edge patch发挥着重要作用。它有助于确定一个物体的结束和另一个物体的开始。这在多个物体重叠或紧密排列的复杂图像中尤为重要。通过分析edge patch，算法可以有效地区分这些物体，从而在自动驾驶、人脸识别和医学成像等任务中获得更准确的结果。此外，edge patch的研究不仅限于检测。它还涉及图像的增强。在图像编辑软件中，用户通常应用专注于edge patch的滤镜来锐化或柔化物体的边缘。这个过程改善了图像的视觉美感，使其对观众更具吸引力。例如，摄影师可能会增强风景照片的edge patch，使树木在天空中更加突出，从而创造出更戏剧性的效果。除了实际应用，edge patch的概念也可以与图像分析的理论方面相关联。研究人员研究不同算法如何处理edge patch以提高性能和准确性。通过理解edge patch的特征，他们可以开发出更好的图像处理技术，以最小化错误并增强输出的整体质量。这项研究在人工智能等领域至关重要，机器学习如何类似于人类解读视觉数据。此外，edge patch的重要性还可以在机器学习领域看到。卷积神经网络（CNN）在图像分类任务中广泛使用，严重依赖于识别edge patch。这些网络通过首先关注边缘来学习识别图像中的模式和特征，而边缘是形状和形式的主要指示器。CNN准确分类图像的能力往往取决于它们检测和解释edge patch的熟练程度。总之，术语edge patch涵盖了图像处理和分析的一个关键方面。无论是在增强图像、识别物体还是开发机器学习算法的背景下，理解edge patch都是基础。随着技术的不断发展，edge patch的重要性只会增加，影响我们与日益数字化的世界中视觉信息的互动和解读。