convolutions

简明释义

英[ˌkɒnvəˈluːʃənz]美[ˌkɑnvəˈluʃənz]

肠曲

英英释义

单词用法

同义词

反义词

例句

1.Leptomeningeal metastasis appear as enhancing curvilinear segments following the gyral convolutions often with small nodular deposits on the surface of the brain.

软脑膜转移表现为紧贴于脑回的曲线样强化段，经常可以看到小结节沉着于脑表面。

2.Compared with the sectioned and graphic convolutions, the method is able not only to express directly the integral functions but to simplify the calculation.

该法与分段卷积法和图解卷积法相比，不仅可直接表达积分函数，而且又能简化卷积计算。

3.The typical use case for Numerical Python is in scientific modeling, or perhaps in related areas such as graphic manipulations and convolutions or signal processing.

Numerical Python的典型用例是科学建模，或者可能是相关领域，比如图形处理和旋转，或者信号处理。

4.Such convolutions leave the reader in a high state of uncertainty about what you just said.

这样拐弯抹角使读者因不能确定你所说的话而十分着急。

5.The typical use case for Numerical Python is in scientific modeling, or perhaps in related areas such as graphic manipulations and convolutions or signal processing.

Numerical Python的典型用例是科学建模，或者可能是相关领域，比如图形处理和旋转，或者信号处理。

6.Convolutions frequently alternate in direction of rotation and vary in pitch.

盘旋经常改变回转方向和节距。

7.On the basis of FPT, in this paper we introduce an iteration algorithm for computing hyper-large scale 2-d cyclic convolutions by combining FPT with FNT.

本文将FPT和FNT相结合提出了一种计算超大型二维循环卷积的迭代算法，它的基础是应用了FPT。

8.I believe in that myself because it has been explained by competent men as the convolutions of the grey matter.

我本人是相信这一点的，因为有识之士已经诠释说，那是脑灰质沟回。

9.I feel the delightful, velvety texture of a flower, and discover its remarkable convolutions; and something of the miracle of Nature is revealed to me.

我摸着花朵上那可爱的天鹅绒般的质地，以及它那叠合巧妙的花苞，于是我领略到了某种大自然的神奇。

10.The plot of the movie had many unexpected convolutions that kept the audience guessing.

这部电影的情节有许多意想不到的曲折，让观众一直猜测。

11.In mathematics, we often deal with the convolutions of functions to analyze their behavior.

在数学中，我们经常处理函数的卷积以分析它们的行为。

12.The convolutions of the brain are essential for its functioning and processing capabilities.

大脑的褶皱对其功能和处理能力至关重要。

13.The artist's painting was filled with intricate convolutions that drew the viewer's eye.

这位艺术家的画作充满了复杂的卷曲，吸引了观众的目光。

14.Her thoughts were a series of convolutions, making it hard for her to focus.

她的思绪是一系列的曲折，让她很难集中注意力。

作文

In the study of mathematics and physics, we often encounter complex problems that require deep understanding and critical thinking. One such concept that frequently arises is the idea of convolutions (卷积). In essence, a convolution is a mathematical operation that combines two functions to produce a third function, representing how the shape of one is modified by the other. This concept is not only pivotal in theoretical studies but also has practical applications in various fields such as engineering, computer science, and signal processing.To illustrate this, let us consider the application of convolutions (卷积) in digital image processing. When we apply filters to images, such as blurring or sharpening, we are essentially using convolutions. The filter, which is a small matrix of numbers, is convolved with the pixel values of the image. This operation modifies the pixel values based on the surrounding pixels, resulting in different visual effects. Without the concept of convolutions (卷积), many of the image processing techniques we take for granted would not be possible.Moreover, convolutions (卷积) play a significant role in machine learning, particularly in the field of deep learning. Convolutional Neural Networks (CNNs) utilize convolutions (卷积) to automatically detect features in data. For instance, in facial recognition systems, CNNs can learn to identify edges, textures, and patterns by applying multiple layers of convolutions. This ability to extract hierarchical features from raw data is what makes CNNs incredibly powerful for tasks involving images and videos.However, the concept of convolutions (卷积) can be quite challenging to grasp, especially for beginners. The mathematical definition involves integrals and sums that may seem daunting at first. It requires a solid understanding of functions and their properties. Yet, once you become familiar with the idea, you will find that convolutions (卷积) provide a robust framework for analyzing and solving complex problems.In addition to its mathematical significance, the term convolutions (卷积) can also be used metaphorically to describe intricate situations in life. Just as mathematical convolutions combine different functions, our experiences often intertwine in complex ways. Life is filled with twists and turns, and sometimes we find ourselves navigating through the convolutions (卷积) of our personal journeys. Understanding this complexity can lead to greater empathy and insight into the human experience.In conclusion, the concept of convolutions (卷积) is essential in both mathematical theory and practical applications. Whether it is through enhancing images, powering machine learning algorithms, or reflecting on the complexities of life, convolutions (卷积) remind us of the interconnectedness of ideas and experiences. As we continue to explore this fascinating topic, we develop not only our technical skills but also a deeper appreciation for the beauty of complexity in both mathematics and life.

在数学和物理的研究中，我们经常会遇到复杂的问题，这些问题需要深入理解和批判性思维。一个经常出现的概念是convolutions（卷积）的思想。本质上，卷积是一种数学运算，它将两个函数结合以产生第三个函数，表示一个函数如何被另一个函数修改。这个概念不仅在理论研究中至关重要，而且在工程、计算机科学和信号处理等各个领域都有实际应用。为了说明这一点，让我们考虑convolutions（卷积）在数字图像处理中的应用。当我们对图像应用滤镜时，例如模糊或锐化，我们本质上是在使用卷积。滤镜是一个小的数字矩阵，它与图像的像素值进行卷积。这个操作根据周围的像素修改像素值，从而产生不同的视觉效果。如果没有convolutions（卷积）的概念，我们所认为理所当然的许多图像处理技术将无法实现。此外，convolutions（卷积）在机器学习中也发挥着重要作用，尤其是在深度学习领域。卷积神经网络（CNN）利用convolutions（卷积）自动检测数据中的特征。例如，在面部识别系统中，CNN能够通过应用多个卷积层来学习识别边缘、纹理和模式。这种从原始数据中提取分层特征的能力使得CNN在涉及图像和视频的任务中极具威力。然而，convolutions（卷积）的概念对于初学者来说可能相当具有挑战性。它的数学定义涉及积分和求和，对于初学者来说可能显得令人生畏。它需要对函数及其属性有扎实的理解。然而，一旦你熟悉了这个概念，你会发现convolutions（卷积）为分析和解决复杂问题提供了一个强大的框架。除了其数学意义外，术语convolutions（卷积）也可以用来比喻地描述生活中错综复杂的情况。就像数学卷积结合不同的函数一样，我们的经历往往以复杂的方式交织在一起。生活充满了曲折，有时我们发现自己在个人旅程的convolutions（卷积）中徘徊。理解这种复杂性可以带来更大的同情心和对人类经验的洞察。总之，convolutions（卷积）的概念在数学理论和实际应用中都是至关重要的。无论是通过增强图像、为机器学习算法提供动力，还是反思生活的复杂性，convolutions（卷积）都提醒我们思想和经历的相互关联。随着我们继续探索这一迷人的主题，我们不仅发展了技术技能，也对数学和生活中的复杂美有了更深的欣赏。