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Network Dissection
Network Dissection lets you examine and measure how well neural networks recognize visual concepts, helping researchers understand deep learning models.
Explore how neural networks interpret visual data
Network Dissection is a research-focused platform that helps you analyze how convolutional neural networks (CNNs) interpret visual information. By evaluating the alignment between hidden units in a neural network and a wide set of semantic concepts, the site offers a unique way to measure interpretability within deep learning models.
If you're interested in understanding what goes on inside CNNs, you can use this framework to score and label neural units based on objects, scenes, textures, and more. The site provides tools and data to compare different models, training methods, and network architectures, making it especially useful for researchers and students in AI and computer vision.
Whether you're testing hypotheses about network interpretability or exploring the effects of various training setups, Network Dissection gives you valuable insights into the inner workings of deep visual models beyond just their accuracy.
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