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In latest years, deep learning has gained a leading role in the pansharpening of multiresolution images. Given the lack of ground truth data, most deep learning-based methods carry out supervised training in a reduced-resolution domain.…
We point out that plasmons in doped graphene simultaneously enable low-losses and significant wave localization for frequencies below that of the optical phonon branch $\hbar\omega_{Oph}\approx 0.2$ eV. Large plasmon losses occur in the…
Hyperspectral imaging offers new perspectives for diverse applications, ranging from the monitoring of the environment using airborne or satellite remote sensing, precision farming, food safety, planetary exploration, or astrophysics.…
This review systematically analyzes patent disclosures regarding plasmonic structures, devices, and integrated applications, highlighting the technology's capability to confine and manipulate electromagnetic energy at the nanoscale. Core…
Partitioning an image into superpixels based on the similarity of pixels with respect to features such as colour or spatial location can significantly reduce data complexity and improve subsequent image processing tasks. Initial algorithms…
In this work, we propose a CNN-based approach to estimate the spectral reflectance of a surface and the spectral power distribution of the light from a single RGB image of a V-shaped surface. Interreflections happening in a concave surface…
Nanoscale phase-control is one of the most powerful approaches to specifically tailor electrical fields in modern nanophotonics. Especially the precise sub-wavelength assembly of many individual nano-building-blocks has given rise to…
Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here we develop and experimentally implement a deep kernel learning workflow combining the correlative…
Physics-driven deep learning (PD-DL) models have proven to be a powerful approach for improved reconstruction of rapid MRI scans. In order to train these models in scenarios where fully-sampled reference data is unavailable, self-supervised…
Self-assembly processes allow us to design and create complex nanostructures using molecules as building blocks and surfaces as scaffolds. This autonomous driven construction is possible due to a complex thermodynamic balance of…
In recent years, the development of nanophotonic devices has presented a revolutionary means to manipulate light at nanoscale. Recently, artificial neural networks (ANNs) have displayed powerful ability in the inverse design of nanophotonic…
3D engineering of matter has opened up new avenues for designing systems that can perform various computational tasks through light-matter interaction. Here, we demonstrate the design of optical networks in the form of multiple diffractive…
One of the most important processes in the fight against current and future pandemics is the rapid diagnosis and initiation of treatment of viruses in humans. In these times, the development of high-sensitivity tests and diagnostic kits is…
Plasmon resonance, with strong coupling of light to electrons at a metal-dielectric interface, allows light confinement and control at subwavelength scale. It's fundamentally limited by the inherent mobility of the electrons, leading to the…
We study and actively control the coherent properties of Surface Plasmon Polaritons (SPPs) optically exited on a nano-hole array. Amplitude and phase of the optical excitation are externally controlled via a digital spatial light modulator…
High-quality flat optical elements require efficient light deflection to large angles and over a wide wavelength spectrum. Although phase gradient metasurfaces achieve this by continuously adding phase shifts in the range of 0 to 2{\pi} to…
Hyperspectral imaging enables versatile applications due to its competence in capturing abundant spatial and spectral information, which are crucial for identifying substances. However, the devices for acquiring hyperspectral images are…
This paper proposes a new deep convolutional neural network (DCNN) architecture that learns pixel embeddings, such that pairwise distances between the embeddings can be used to infer whether or not the pixels lie on the same region. That…
The use of fluorescent molecules to create long sequences of low-density, diffraction-limited images enables highly-precise molecule localization. However, this methodology requires lengthy imaging times, which limits the ability to view…
We demonstrate intracavity plasmonic laser spectroscopy using a plasmonic laser created from a periodically-perforated silver film with a liquid gain medium. An active zone of the laser is formed by a highly elongated spot of pumping. This…