Split Computing for Vision Transformers in Automotive MEC

Analyzing cut-layer selection in hierarchical Swin and ViT backbones, measuring bottleneck feature bandwidth trade-offs against cellular packet transmission delays.

Bottleneck Autoencoder Feature Compression

Lightweight onboard convolutional autoencoders compress attention patch tokens by 16x before radio transmission, reconstructed on MEC GPUs with less than 0.5% detection mAP degradation.

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