#017 CNN Inception Network
\(Inception\enspace network \) Motivation for the \(Inception\enspace network \): In the last post we talked about why \(1\times 1 \) convolutional layer can be useful and now we will use it for building the \(Inception\enspace network \). When designing a layer for a \(convnet \) we might have to choose between a \(1 \times 3 \) filter, a \(3 \times 3\) or \(5\times 5\) or maybe a pooling layer. An \(Inception\enspace network \) solves this…
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