Deep Learning Image Transmission Through a Multi-mode Fiber

Date

2019-09-06

Author

Kürekci, Şahin
Odabaş, M. Ekrem
Yüce, Emre

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

139
views

0
downloads

URI

https://hdl.handle.net/11511/92507

Conference Name

21. Ulusal Optik, Elektro-Optik ve Fotonik Çalıştayı

Collections

Department of Physics, Conference / Seminar

Suggestions

OpenMETU
Core

Deep learning-based image transmission through a multi-modefiber Kürekçi, Şahin; Odabaş, Ekrem; Temur, Tarık; Afshari, Gilda; Yüce, Emre (null; 2020-04-09) Image transmission through a multi-mode fiber is a difficult task given the complex interference of light through the fiber that leads to random speckle patterns at the distal end of the fiber. With traditional methods and techniques, it is impractical to reconstruct a high-resolution input image by using the information obtained from the intensity of the corresponding output speckle alone. In this work, we train three Convolutional Neural Networks (CNNs) with input-output couples of a multi-mode fiber and ...
Deep Learning Based Speed Up of Fluid Dynamics Solvers Acar, Deniz Alper; Uzol, Oğuz; Department of Aerospace Engineering (2022-9-8) In this thesis, two distinct deep learning-based methods for the speed-up of fluid dynamics solvers are proposed. The first method called Parametric Encoded Physics informed neural network (PEPINN), is utilized to solve transient fluid dynamics problems. PEPINN is an alternative to the Physics informed neural networks (PINN) and is based on the parametric encoding of the problem domain. In PEPINN the automatic differentiation for calculation of the problem residual is replaced with finite difference kernel...
Deep Learning with Multivariate Adaptive Regression Spline with Bagging Methods Kaygusuz, Mehmet Ali; Somuncuoğlu, Abdullah Nuri; Purutçuoğlu Gazi, Vilda (2021-09-01)
Deep learning-based spectral splitting and concentration of broadband light for solar cells applications Yolalmaz, Alim; Yüce, Emre (2020-11-30)
Deep image compression with a unified spatial and channel context auto-regressive model Uludağ, Ali Sefkan; Kamışlı, Fatih; Department of Electrical and Electronics Engineering (2022-8) Recently, variational auto-encoder-based compression models have gained much attention in learned image compression field due to their dimension reduction property. These models have three essential components which are encoder, decoder and entropy network. Encoder part of the VAE transforms a high dimensional space to a lower dimensional latent space, whereas the decoder serves as a reconstructing transformation. The entropy model is trained to generate the probability distributions of the latent represent...

Citation Formats

Ş. Kürekci, M. E. Odabaş, and E. Yüce, “Deep Learning Image Transmission Through a Multi-mode Fiber,” presented at the 21. Ulusal Optik, Elektro-Optik ve Fotonik Çalıştayı, İstanbul, Türkiye, 2019, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/92507.