A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...
Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...
High resolution and sensitivity are critical in nuclear magnetic resonance (NMR) spectroscopy. Both can be overdoubled when using heteronuclear decoupling. This enables the severance of overlapping ...
AI-powered spectral sensor performs machine learning during light capture, identifying materials and chemicals in real time ...
The review discusses innovations in quartz-enhanced laser spectroscopy, emphasizing QEPAS and LITES for improved sensitivity ...
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