Experimental Validation of Spectral-Spatial Power Evolution Design Using Raman Amplifiers
We experimentally validate a machine learning-enabled Raman amplification framework, capable of jointly shaping the signal power evolution in two domains: frequency and fiber distance. The proposed experiment addresses the amplification in the whole C-band, by optimizing four first-order counter-propagating Raman pumps.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningSimilar Papers 제목 키워드 기반
Experimental validation of machine-learning based spectral-spatial power evolution shaping using Raman amplifiers
We experimentally validate a real-time machine learning framework, capable of controlling the pump power values of Raman amplifiers to shape the signal power evolution in two-dimensions (2D): frequency and fiber distance…
Multi-Fake Evolutionary Generative Adversarial Networks for Imbalance Hyperspectral Image Classification
This paper presents a novel multi-fake evolutionary generative adversarial network(MFEGAN) for handling imbalance hyperspectral image classification. It is an end-to-end approach in which different generative objective l…
ClassificationGenerative Adversarial NetworkHyperspectral Image Classificationimage-classification+1Non-collocated vibration absorption using delayed resonator for spectral and spacial tuning -- analysis and experimental validation
Non-collocated vibration absorption (NCVA) concept using delayed resonator for in-situ tuning is analyzed and experimentally validated. There are two critical contributions of this work. One is on the scalable analytical…
Semantic segmentation of multispectral photoacoustic images using deep learning
Photoacoustic (PA) imaging has the potential to revolutionize functional medical imaging in healthcare due to the valuable information on tissue physiology contained in multispectral photoacoustic measurements. Clinical …
Deep LearningSegmentationSemantic SegmentationTranslationSpectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
Recent research has shown that using spectral–spatial information can considerably improve the performance of hyperspectral image (HSI) classification. HSI data is typically presented in the format of 3D cubes. Thus, 3D …
ClassificationFew-Shot Image ClassificationHyperspectral Image Classification