Search Results - "Qasim, Shah Rukh"
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Learning representations of irregular particle-detector geometry with distance-weighted graph networks
Published in The European physical journal. C, Particles and fields (01-07-2019)“…We explore the use of graph networks to deal with irregular-geometry detectors in the context of particle reconstruction. Thanks to their…”
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Multi-particle reconstruction in the High Granularity Calorimeter using object condensation and graph neural networks
Published in EPJ Web of conferences (2021)“…The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of…”
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Journal Article Conference Proceeding -
3
End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks
Published in The European physical journal. C, Particles and fields (01-08-2022)“…We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that…”
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Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics
Published in Frontiers in big data (12-01-2021)“…Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet…”
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End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks
Published 30-09-2022“…Eur. Phys. J. C 82, 753 (2022) We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular…”
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6
Learning representations of irregular particle-detector geometry with distance-weighted graph networks
Published 24-07-2019“…Eur. Phys. J. C, 79 7 (2019) 608 We explore the use of graph networks to deal with irregular-geometry detectors in the context of particle reconstruction…”
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GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter
Published 02-03-2022“…We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used…”
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8
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics
Published 04-02-2021“…Frontiers in Big Data 3 (2021) 44 Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as…”
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Rethinking Table Recognition using Graph Neural Networks
Published in 2019 International Conference on Document Analysis and Recognition (ICDAR) (01-09-2019)“…Document structure analysis, such as zone segmentation and table recognition, is a complex problem in document processing and is an active area of research…”
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Conference Proceeding -
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Tracking of charged particles with nanosecond lifetimes at LHCb
Published in The European physical journal. C, Particles and fields (30-07-2024)“…A method is presented to reconstruct charged particles with lifetimes between 10 ps and 10 ns , which considers a combination of their decay products and the…”
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Study of b-hadron decays to Λc+h−h′− final states
Published in The journal of high energy physics (2024)“…A bstract Decays of Ξ b − and Ω b − baryons to Λ c + h − h ′ − final states, with h − h ′− being π − π − , K − π − and K − K − meson pairs, are searched for…”
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Table Detection Using Deep Learning
Published in 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) (01-11-2017)“…Table detection is a crucial step in many document analysis applications as tables are used for presenting essential information to the reader in a structured…”
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Conference Proceeding -
13
Rethinking Table Recognition using Graph Neural Networks
Published 30-05-2019“…Document structure analysis, such as zone segmentation and table recognition, is a complex problem in document processing and is an active area of research…”
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Journal Article -
14
Multi-particle reconstruction in the High Granularity Calorimeter using object condensation and graph neural networks
Published 02-06-2021“…The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of…”
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Journal Article