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Cluster Reconstruction in Electromagnetic Calorimeters Using Machine Learning Methods
Kalina Dimitrova, Venelin Kozhuharov, Ruslan Nastaev +1
Machine-learning-based methods can be developed for the reconstruction of clusters in segmented detectors for high energy physics experiments. Convolutional neural networks with au…
Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors
Kalina Dimitrova, Venelin Kozhuharov, Peicho Petkov
Machine learning methods are being introduced at all stages of data reconstruction and analysis in various high-energy physics experiments. We present the development and applicati…
Multigap RPC for PET: development and optimisation of the detector design
Georgi Georgiev, Nevena Ilieva, Venelin Kozhuharov +4
Transforming the resistive plate chambers from charged-particle into gamma-quanta detectors opens the way towards their application as a basic element of a hybrid imaging system, w…