Optical Data Analysis: Decoding Optical Data with Machine Learning (Laser Photonics Rev. 15(2)/2021)

Optical data self-routing using address decoding

We present an optoelectronic self-routing packet switch for digital data commutation applications. The routing of the input data is determined by the optical decoding of the destination address coded in the packet header preceding the data bits. As proof of the operating principle, a one input 64 output demonstration system was built. The experiment is based on the association of

control of the optical properties of nanoparticles by laser fields

در این پایان نامه، درهمتنیدگی بین یک سیستم نقطه کوانتومی دوگانه(مولکول نقطه کوانتومی) و میدان مورد مطالعه قرار گرفته است. از آنتروپی ون نیومن به عنوان ابزاری برای بررسی درهمتنیدگی بین اتم و میدان استفاده شده و تاثیر پارامترهای مختلف، نظیر تونل زنی(که توسط تغییر ولتاژ ایجاد می شود)، شدت میدان و نسبت دو گسیل خودبخودی بر رفتار درجه درهمتنیدگی سیستم بررسی شده اشت.با تغییر هر یک از این پارامترها، در...

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Learning Optical Flow from Real Robot Data

This project presents a method for teaching robot arms optical flow. By extending recent works on depth based, probabilistic robot tracking, a novel real-world optical flow dataset with dense ground truth annotation is generated. A real, robotic dataset boasts the inclusion of phenomena that synthetic datasets cannot model. With this data a generic convolutional neural network is implemented to...

Analysis of Dynamic Optical Imaging Data