Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here...
An integrated experimental-computational strategy for the accurate characterization of the conformational landscape of flexible biomolecule building blocks is proposed. This is based on the combination of rotational spectroscopy with quantum-chemical...
Imaging in visible and short-wave infrared (SWIR) wavebands is essential in most remote sensing applications. However, compared to visible imaging cameras, SWIR cameras typically have lower spatial resolution, which limits the detailed information sh...
Bacteria, especially foodborne pathogens, seriously threaten human life and health. Rapid discrimination techniques for foodborne pathogens are still urgently needed. At present, laser-induced breakdown spectroscopy (LIBS), combined with machine lear...
In this Letter, we propose an attention-based neural network specially designed for the challenging task of polarimetric image denoising. In particular, the channel attention mechanism is used to effectively extract the features underlying the polari...
The affordable, accurate, and generalizable prediction of spectroscopic observables plays a key role in the analysis of increasingly complex experiments. In this article, we develop and deploy a deep neural network-XANESNET-for predicting the linesha...
A Mueller matrix (MM) provides a comprehensive representation of the polarization properties of a complex medium and encodes very rich information on the macro- and microstructural features. Histopathological features can be characterized by polariza...
We propose a polarimetric imaging processing method based on feature fusion and apply it to the task of target detection. Four images with distinct polarization orientations were used as one parallel input, and they were fused into a single feature m...
SIGNIFICANCE: Biomedical optics system design, image formation, and image analysis have primarily been guided by classical physical modeling and signal processing methodologies. Recently, however, deep learning (DL) has become a major paradigm in com...
SIGNIFICANCE: The non-destructive characterization of cardiac tissue composition provides essential information for both planning and evaluating the effectiveness of surgical interventions such as ablative procedures. Although several methods of tiss...