Photonics, Free Full-Text

Photons Counted Integral Imaging (PCII) reconstructs 3D scenes with both focused and off-focused voxels. The off-focused portions do not contain or convey any visually valuable information and are therefore redundant. In this work, for the first time, we developed a six-ensembled Deep Neural Network (DNN) to identify and remove the off-focused voxels from both the conventional computational integral imaging and PCII techniques. As a preprocessing step, we used the standard Otsu thresholding technique to remove the obvious and unwanted background. We then used the preprocessed data to train the proposed six ensembled DNNs. The results demonstrate that the proposed methodology can efficiently discard the off-focused points and reconstruct a focused-only 3D scene with an accuracy of 98.57%.

Graphene Photonics

Springer Handbook of Electronic and Photonic Materials

Creating large Fock states and massively squeezed states in optics using systems with nonlinear bound states in the continuum

Graphene Photonics, Plasmonics, and Broadband Optoelectronic Devices

Empowering Metasurfaces with Inverse Design: Principles and Applications

Photonics Focus Magazine Vol. 3 Issue 2

Programmable photonic circuits

An integrated photonics engine for unsupervised correlation detection

Events - LIGENTEC

Open Access Research on High-speed free-space optical communication using standard fiber communication components without optical amplification (Full -Text)

Photonics June 2023 - Browse Articles

Photonics Spectra Conference 2022: January 10 - 13, Webinars

Optics and Photonics: Essential Technologies for Our Nation