图 书 馆
机器视觉的深度学习Deep Learning for Machine Vision |
|
| 课程网址: | http://videolectures.net/bmvc2013_coates_machine_vision/ |
| 主讲教师: | Adam Coates |
| 开课单位: | 百度公司 |
| 开课时间: | 2014-04-03 |
| 课程语种: | 英语 |
| 中文简介: |  机器学习算法使从业者摆脱了许多容易出错的，手工设计的组件，从而可以在常见的机器视觉任务（例如对象识别）中做出决策。然而，困难的主要根源在于，这样的学习系统仍然依赖于许多手工构建的组件，例如复杂的特征提取器，它们试图识别图像中高级学习模式无法自行发现的高级模式。 “深度学习”和“表示学习”算法旨在通过从数据中自动学习更高级别的表示来消除这一障碍，并已在视觉，语音和语言任务方面取得了近期成功。本教程将介绍深度学习算法的基本组成部分以及用于调试并将这些方法应用于机器视觉问题的实用技术。本教程的第一部分将介绍神经网络模型和基本训练方法，包括误差反向传播和数值优化方法，其中以图像分类为动力。第二部分将介绍其他（有时是特定于域的）技术，以提高这些算法的性能并将其应用于其他视觉任务，包括检测和图像分割。借助这些工具，观众将了解到深度学习算法的工作原理以及如何在实际应用中使用深度学习算法，并且具有足够的知识来完成在线上可用的教程。最后，我们将简要概述深度学习研究中的其他重要主题和结果。 |
| 课程简介: | Machine learning algorithms have freed practitioners from many error-prone, hand-engineered components for making decisions in common machine vision tasks such as object recognition. A major source of difficulty, however, is that such learning systems still rely on many hand-built components like sophisticated feature extractors that attempt to identify higher-level patterns in images that typical learning algorithms cannot discover on their own. "Deep learning" and "representation learning" algorithms aim to remove this hurdle by learning higher-level representations automatically from data and have led to recent successes in vision, speech, and language tasks. This tutorial will introduce the basic components of deep learning algorithms and practical techniques for debugging and applying these methods to machine vision problems. The first part of the tutorial will cover neural network models and basic training approaches including error back-propagation and numerical optimization methods, with image classification as a motivating application. The second part will cover additional (sometimes domain-specific) techniques to improve the performance of these algorithms and apply them to other vision tasks including detection and image segmentation. With these tools, audience members will understand how deep learning algorithms work and how they are used in practical applications with sufficient knowledge to complete a hands-on tutorial available on the web. We will conclude with a brief high-level overview of other important topics and results in deep learning research. |
| 关 键 词: | 计算机视觉; 机器学习; 数据算法 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-06-11：吴淑曼 |
| 最后编审: | 2020-06-11：吴淑曼(课程编辑志愿者) |
| 阅读次数: | 62 |