arXiv 2004.150042020-04cs.HCcs.AIcs.CVcs.LG

CNN Explainer：使用交互式可视化学习卷积神经网络

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization

Georgia Tech（佐治亚理工学院）；Oregon State University（俄勒冈州立大学）

Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng Chau

备注：: 11 pages, 14 figures, to be presented at IEEE VIS 2020. For a demo video, see https://youtu.be/HnWIHWFbuUQ . For a live demo, visit https://poloclub.github.io/cnn-explainer/
DOI：: 10.1109/TVCG.2020.3030418

摘要：

深度学习的巨大成功激励着许多从业者和学生学习这项令人兴奋的技术。然而，由于理解和应用深度学习的复杂性，初学者迈出第一步往往具有挑战性。我们介绍了CNN解释器，这是一个交互式可视化工具，专为非专家学习和检查卷积神经网络（CNN）而设计，CNN是一种基础深度学习模型架构。我们的工具解决了新手在学习CNN时面临的关键挑战，我们从对教师的采访和对过去学生的调查中发现了这些挑战。CNN解释器紧密集成了一个模型概述，总结了CNN的结构，以及按需动态视觉解释视图，帮助用户理解CNN的底层组件。通过抽象层次之间的平滑过渡，我们的工具使用户能够检查低级数学运算和高级模型结构之间的相互作用。一项定性的用户研究表明，CNN解释器可以帮助用户更容易地理解CNN的内部工作原理，并且使用起来非常有趣。我们也从我们的研究中获得设计经验。CNN Explainer使用现代Web技术开发，在用户的Web浏览器中本地运行，无需安装或专用硬件，从而扩大了公众对现代深度学习技术的教育访问。

英文摘要：

Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying deep learning. We present CNN Explainer, an interactive visualization tool designed for non-experts to learn and examine convolutional neural networks (CNNs), a foundational deep learning model architecture. Our tool addresses key challenges that novices face while learning about CNNs, which we identify from interviews with instructors and a survey with past students. CNN Explainer tightly integrates a model overview that summarizes a CNN's structure, and on-demand, dynamic visual explanation views that help users understand the underlying components of CNNs. Through smooth transitions across levels of abstraction, our tool enables users to inspect the interplay between low-level mathematical operations and high-level model structures. A qualitative user study shows that CNN Explainer helps users more easily understand the inner workings of CNNs, and is engaging and enjoyable to use. We also derive design lessons from our study. Developed using modern web technologies, CNN Explainer runs locally in users' web browsers without the need for installation or specialized hardware, broadening the public's education access to modern deep learning techniques.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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