Design 'EfficientDenseNet' — a DenseNet variant under 10M params that incorporates VoVNet-style one-shot aggregation (OSA), depthwise separable bottlenecks, squeeze-and-excitation attention, LayerNorm pre-activation, and aggressive compound scaling. The goal is to train 2-3× faster than DenseNet-121 while maintaining or improving accuracy on ImageN

Design an enhanced ConvNeXt V2 architecture incorporating multi-scale dynamic convolutions, adaptive feature recalibration via a lightweight coordinate-aware gating mechanism, and a refined pretraining strategy (improved FCMAE with spatial-aware masking and hierarchical reconstruction loss) to improve representation quality and downstream performan