CDPM-Align applies multi-scale guidance-aligned conditional diffusion pretraining on three small heterogeneous datasets to improve accuracy and uncertainty in few-shot (10-25 image) anatomical landmark detection.
IEEE Trans
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SwitchBraidNet is a compact dual-path EEG classifier achieving 69.49% MI accuracy (FP16), 93.48% SSVEP accuracy (FP32), 64.82 bits/min hybrid ITR (FP16), and 3.03 KB INT8 size via quantization-aware training on OpenBMI.
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CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection
CDPM-Align applies multi-scale guidance-aligned conditional diffusion pretraining on three small heterogeneous datasets to improve accuracy and uncertainty in few-shot (10-25 image) anatomical landmark detection.
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SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface
SwitchBraidNet is a compact dual-path EEG classifier achieving 69.49% MI accuracy (FP16), 93.48% SSVEP accuracy (FP32), 64.82 bits/min hybrid ITR (FP16), and 3.03 KB INT8 size via quantization-aware training on OpenBMI.