AIMC Topic: Light

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A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

PloS one
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability...

Evaluation of extra virgin olive oil stability by artificial neural network.

Food chemistry
The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions was evaluated. The following analyses were carried out: free fatty acids, peroxide value, specific ext...

Machine learning-guided fabrication of carbon dot-pepsin nano-conjugates for enhanced bioimaging, synergistic drug delivery, and visible light-induced photosensitization.

Nanoscale
Carbon dots (CDs) are emerging as next-generation bioimaging agents due to their strong fluorescence, photobleaching resistance, and biocompatibility. However, their small size often limits efficient cell internalization, leading to unspecified cellu...

Unsupervised Adaptive Deep Learning Framework for Video Denoising in Light Scattering Imaging.

Analytical chemistry
Light scattering is a powerful tool that has been widely applied in various scenarios, such as nanoparticle analysis, single-cell measurement, and blood flow monitoring. However, noise is always a concerning and challenging issue in light scattering ...

Enhancing 3D human pose estimation with NIR single-pixel imaging and time-of-flight technology: a deep learning approach.

Journal of the Optical Society of America. A, Optics, image science, and vision
The extraction of 3D human pose and body shape details from a single monocular image is a significant challenge in computer vision. Traditional methods use RGB images, but these are constrained by varying lighting and occlusions. However, cutting-edg...

Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Appropriate skin treatment and care warrants an accurate prediction of skin moisture. However, current diagnostic tools are costly and time-consuming. Stratum corneum moisture content has been measured with moisture content meters or from...

A machine learning potential for simulating infrared spectra of nanosilicate clusters.

The Journal of chemical physics
The use of machine learning (ML) in chemical physics has enabled the construction of interatomic potentials having the accuracy of ab initio methods and a computational cost comparable to that of classical force fields. Training an ML model requires ...

Tunable grating surfaces with high diffractive efficiency optimized by deep neural networks.

Optics letters
High diffractive efficiency gratings, as a core component in optics, can engineer light transport and separation. This Letter predicts a grating surface with high diffractive efficiency within the visible light wave band with the aid of deep neural n...

Measuring laser beams with a neural network.

Applied optics
A deep neural network (NN) is used to simultaneously detect laser beams in images and measure their center coordinates, radii, and angular orientations. A dataset of images containing simulated laser beams and a dataset of images with experimental la...