SpecCL: spectral-guided contrastive learning for animal activity recognition using tri-axial accelerometer signals
Spectral-Guided Contrastive Learning (SpecCL), a novel physics-informed SSL framework, is proposed, which introduces sensor-realistic augmentations to construct physically meaningful learning pairs simulating real-world perturbations and distills physical priors into the learned temporal representations.