Decoding Convolution
Explore the concept of convolution and how it functions as a pattern detection tool in convolutional neural networks. Understand how filters are applied to images, such as recognizing the number "2," to extract meaningful features. This lesson builds foundational knowledge on convolution's role in automating feature learning within deep learning architectures.
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Convolution is a cornerstone operation in deep learning, particularly in the field of image processing and recognition. The concept might seem intricate at first glance, but it becomes more approachable when illustrated through practical examples. In this lesson, we’ll demystify convolution by exploring how it’s applied in a common deep learning task: image recognition.
Problem
Consider an image of the number “2.” To a human, identifying this numeral is almost instantaneous, but for a machine, the task requires a systematic approach to recognize patterns and shapes that define “2.” This is where convolution comes into play. The objective and challenge are to train a machine to perform the task, for which one approach is “filtration.”
Filtration
There are several ways to perform letter “2” detection. One of them is learning distinctive filters and filtering an image through them. The filters should have shapes that distinguish “2.” One such set of filters is ...