APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -The first layer is responsible for capturing the low-level features such as colour, edges, gradient orientation etc. Conventional Convolution Layer – This layer receives a single input which is a feature map and it computes its output by convolving filters across the feature maps from the previous layer.
Detailed explanation-2: -Convolutional Layer is the first layer in a CNN. It gets as input a matrix of the dimensions [h1 * w1 * d1], which is the blue matrix in the above image.
Detailed explanation-3: -In the 1980s, the world saw its first CNN developed by postdoctoral computer science researcher Yann LeCun. It was built to recognize handwritten digits. The NN architecture was straightforward, with five layers of 5x5 convolutional layers and 2x2 max-pooling. It was named as LeNet after Yann LeCun himself.