Convolutional neural network forward pass sequence from input tensor through three progressive convolution blocks with 32, 64, and 128 filters, followed by flatten and fully connected layers for 4-class classification. The diagram traces data flow through Phase 1 input ingestion, Phase 2-4 convolution processing with activation functions, and Phase 5 flatten-to-output classification. This architecture demonstrates the standard CNN pattern for image feature extraction and hierarchical representation learning. Fork this diagram on Diagrams.so to customize filter counts, add batch normalization, or adapt for your dataset dimensions and class count.