A ______________ is a small matrix used in convolutional layers to detect patterns in the input data.

A kernel (also known as a filter) is a small matrix used in convolutional layers to detect patterns in the input data. In convolutional neural networks (CNNs), kernels slide over the input data (such as images) to produce feature maps, which highlight various features such as edges, textures, or shapes. The size of the kernel determines the scale of the features being detected, and multiple kernels can be used to capture a variety of features at different scales.

The convolution operation involves element-wise multiplication of the kernel with the input data, followed by a summation of the results. This process allows the network to learn relevant features automatically during the training phase, making CNNs particularly effective for image processing tasks.