: Introduces non-linearity by zeroing out negative values, mimicking how biological neurons fire only above certain thresholds.
: Downsample the data to reduce its size, making the model faster and less prone to overfitting. xcnnpz.png
The "deep" nature of the model in the image comes from its stacked layer structure, which acts as a filter to extract meaning: : The raw image pixels (e.g., : Introduces non-linearity by zeroing out negative values,
: The final decision-maker that takes all the extracted features to classify the image as a specific object, like a "cat" or "car". Convolutional Neural Networks & Computer Vision - KNIME and dark spots.
: Use mathematical "kernels" to detect low-level features like edges, lines, and dark spots.