Beam Detection Based on Machine Learning Algorithms
arXiv:2308.00718v1h-index: 7
Originality Synthesis-oriented
AI Analysis
This addresses beam detection for free electron laser applications, but it is incremental as it combines existing methods like VGG16 and support vector regression.
The paper tackled the problem of precisely determining free electron laser beam positions on screens by using a sequence of machine learning models, achieving 85.8% correct prediction on test data.
The positions of free electron laser beams on screens are precisely determined by a sequence of machine learning models. Transfer training is conducted in a self-constructed convolutional neural network based on VGG16 model. Output of intermediate layers are passed as features to a support vector regression model. With this sequence, 85.8% correct prediction is achieved on test data.