Abstract
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.
Users can interactively visualize and inspect the data transformation and flow
of intermediate results in a CNN. 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 operations (e.g., mathematical
computations) and high-level outcomes (e.g., class predictions). To better
understand our tool's benefits, we conducted a qualitative user study, which
shows that CNN Explainer can help 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.
Users
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