[Verse 1]
Started back in eighty-nine with LeCun's dream
LeNet Five showed us what convolution means
Filters slide across the image, stride by stride
Receptive fields are windows where the features hide
Padding keeps the edges safe from being lost
Dilation spreads the kernel out, but at what cost
[Chorus]
Conv Net blues, from pixels to predictions
Kernel slides with mathematical precision
Pooling down, feature maps grow deeper
Transfer learning makes the training cheaper
From LeNet to EfficientNet we climb
Convolutional rhythms keeping time
[Verse 2]
AlexNet brought the power with its GPU might
Eight layers deep and ReLU brought the light
Then VGG went deeper with those tiny threes
Sixteen layers stacked up like autumn leaves
But gradients would vanish in the deeper nets
Until ResNet came along with skip connections set
[Chorus]
Conv Net blues, from pixels to predictions
Kernel slides with mathematical precision
Pooling down, feature maps grow deeper
Transfer learning makes the training cheaper
From LeNet to EfficientNet we climb
Convolutional rhythms keeping time
[Bridge]
ImageNet pretrained weights are gold
Fine-tune the top, keep the bottom bold
Freeze the features, train the classifier
YOLO sees objects, Faster R-CNN's wiser
U-Net segments with that hourglass flow
Encoder-decoder, watch the pixels grow
[Verse 3]
EfficientNet scaled up with compound wisdom
Width and depth and resolution's kingdom
Mobile architectures for the edge device
Separable convolutions, efficient and precise
Object detection with those anchor boxes
Semantic segmentation, pixel-level foxes
[Chorus]
Conv Net blues, from pixels to predictions
Kernel slides with mathematical precision
Pooling down, feature maps grow deeper
Transfer learning makes the training cheaper
From LeNet to EfficientNet we climb
Convolutional rhythms keeping time
[Outro]
Thirty years of vision, layer by layer
Convolution revolution, we're the players
In this neural network, blues-filled game
Computer vision will never be the same