Engage with Deep Learning

Understanding Transposed Convolution Operations in Neural Networks

Transposed convolutions are a particular type of upsampling technique often used in neural networks, particularly GANs.

Just like other upsampling techniques, transposed convolutions increase the size of data. For image data, transposed convolutions are used to increase image dimensions.

Navigating the Application

To make the most of your experience, here are some pointers for using the app:

• Try various input and filter sizes to see their impact on the overall process. 🖱️
• Use the intermediates to understand how the final result is calculated. 🧠
• Transposed convolutions make use of filters with a defined filter size, stride, and padding. This demo assumes no padding and a stride of 1.
• While the app is mobile-friendly, it shines on a desktop. We've done limited testing on mobile devices—please report any issues you encounter. 📱💻