CNN Exam Questions and Answers 100% Pass

CNN Exam Questions and Answers 100% Pass 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