CNN questions and answers with solutions
2024
Convolutional neural networks (CNNs) - ANSWER In machine learning, a convolutional neural network
(CNN, or ConvNet) is a class of deep, feed-forward artificial neural network that have successfully been
applied to analyzing visual imagery.
It's the first layer to extract features from an input img.
CNN image classifications - ANSWER Take an input image, process it and classify it under certain
categories. Computer sees an input image as array of pixels and it depends on the image resolution.
Based on the image resolution, it will see h x w x d( h = Height, w = Width, d = Dimension ).
RGB (3 CHANNELS) - ANSWER An image of 6 x 6 x 3 array of matrix
Grayscale - ANSWER An image of 4 x 4 x 1 array of matrix
CNN - ANSWER Each input image will pass it through a series of convolution layers with filters (Kernals),
Pooling, fully connected layers (FC) and apply Softmax function to classify an object with probabilistic
values between 0 and 1.
Neural network with many convolutional layers - ANSWER a)input
b) feature learning:
- convo + relu
- poopling
- convo + relu
- pooling
c) classification
- flatten
- fully connected
-softmax
2024
Convolutional neural networks (CNNs) - ANSWER In machine learning, a convolutional neural network
(CNN, or ConvNet) is a class of deep, feed-forward artificial neural network that have successfully been
applied to analyzing visual imagery.
It's the first layer to extract features from an input img.
CNN image classifications - ANSWER Take an input image, process it and classify it under certain
categories. Computer sees an input image as array of pixels and it depends on the image resolution.
Based on the image resolution, it will see h x w x d( h = Height, w = Width, d = Dimension ).
RGB (3 CHANNELS) - ANSWER An image of 6 x 6 x 3 array of matrix
Grayscale - ANSWER An image of 4 x 4 x 1 array of matrix
CNN - ANSWER Each input image will pass it through a series of convolution layers with filters (Kernals),
Pooling, fully connected layers (FC) and apply Softmax function to classify an object with probabilistic
values between 0 and 1.
Neural network with many convolutional layers - ANSWER a)input
b) feature learning:
- convo + relu
- poopling
- convo + relu
- pooling
c) classification
- flatten
- fully connected
-softmax