konvoluatiokerros
Konvoluatiokerros, often translated as convolutional layer, is a fundamental building block in artificial neural networks, particularly those used for image processing and computer vision tasks. Its primary function is to extract local features from input data, such as images, by applying a set of learnable filters. Each filter, also known as a kernel, is a small matrix of weights that slides over the input data. At each position, the filter performs an element-wise multiplication with the corresponding portion of the input and sums the results, producing a single value in the output feature map.
This sliding operation, known as convolution, allows the layer to detect patterns like edges, corners, or textures,