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%.

Introducing Photonics

Single-photon microwave photonics - ScienceDirect

Deep learning for the design of photonic structures

Optical meta-waveguides for integrated photonics and beyond

In situ 3D nanoprinting of free-form coupling elements for hybrid photonic integration

Photonics Spectra Conference 2022: January 10 - 13, Webinars

Laser & Photonics Reviews: Vol 17, No 11

Photonics June 2023 - Browse Articles

Photonics, Free Full-Text