Translations:ImageNet Classification with Deep CNNs/10/en

The network processes 224x224 RGB images. The first convolutional layer applies 96 kernels of size 11x11 with stride 4, dramatically reducing the spatial dimensions. Subsequent layers use smaller kernels (5x5 and 3x3). The architecture was split across two GPUs, with each GPU processing half of the feature maps, and cross-GPU communication occurring only at certain layers.