25 citations · 25 across the 1 of their papers we have counts for
3 papers
physics.ins-det2024
Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +48
To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to se…
physics.ins-det2024
Software Compensation for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +61
A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event in…
physics.ins-det2017★ 25 cited
Tracking within Hadronic Showers in the CALICE SDHCAL prototype using a Hough Transform Technique
The CALICE Collaboration
The high granularity of the CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) provides the capability to reveal the track segments present in hadronic showers. These segments are t…