Operations in Convolutional Neural Networks | Convolution, Pooling and Fully Connected Layer
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YouTubeUncomplicatingTech
Operations in Convolutional Neural Networks | Convolution, Pooling and Fully Connected Layer
Learn about the steps involved in CNNs after an image is transformed into a pixel matrix. The pixel matrix goes through convolutional layer which extracts detailed features, then an activation functions is applied on it to convert the matrix into smaller matrix with important features. Then the fully connected layer is a neural network which ...
35.9K viewsOct 24, 2023
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Neural AI on Instagram: "Convolutions are math operations commonly used in deep learning, specifically in convolutional neural networks (CNNs). They work by sliding a small matrix (grid of values), called a kernel or filter, over the input image to extract important features such as edges, textures, or shapes. At each position, the kernel performs an element-wise multiplication with the underlying pixels and sums the result to produce a single output value, forming a feature map that highlights
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