Login

1st AI-INFN User Forum

11–12 Jun 2024
Plesso Berti Pichat
Europe/Rome timezone

Contact

Contribution List

15 out of 15 displayed
Export to PDF
  1. 1. Welcome and introduction
    Lucio Anderlini (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 14:30
  2. 2. INFN-CNAF: status and perspectives
    Luca Dell'Agnello (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 14:40
  3. 14. Enhancing Nodule segmentation Utilizing Attention U-Net: Insights from LUNA-16 Dataset
    Arman Zafaranchi (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 15:00

    Abstract
    Lung cancer remains a significant global health challenge, with early detection playing a critical role in improving patient outcomes. Computed Tomography (CT) imaging has become a cornerstone in the early diagnosis and staging of lung cancer, allowing for the detection of pulmonary nodules that may indicate malignancy. However, accurately segmenting and characterizing these nodules...

    Go to contribution page
  4. 8. Use of a UNet network for the identification of cavities inside mines
    Mr Andrea Paccagnella (Istituto Nazionale di Fisica Nucleare Firenze)
    11/06/2024, 15:25

    Muon radiography is a technique that utilizes muons from cosmic rays to investigate otherwise hard-to-reach environments. This technique offers several advantages, including the absence of accelerators to generate particles that interact with the target under examination. It is a non-invasive technique, both for humans and the observed object. Furthermore, due to the muons' ability to...

    Go to contribution page
  5. 9. Benchmarking image segmentation on AMD-Xilinx FPGAs
    Ms Valentina Sisini (INFN and University of Ferrara)
    11/06/2024, 15:50

    In the context of scientific computing there is a growing interest
    towards DNNs (Deep Neural Networks), which are being used in several
    applications, spanning from medical images segmentation and
    classification, to the on-line analysis of experimental data.
    In addition to GPUs, FPGAs are also emerging as compute accelerators
    promising higher energy-efficiency and lower latency, for the...

    Go to contribution page
  6. 13. HERD data classification
    Luca Tabarroni (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 16:45

    The growing demand for GPUs has led to rapid development of machine learning research techniques in all areas of science, including High Energy Physics. We present a study focused on the classification task of simulated electrons and protons detected by the HERD detector. HERD is a high-energy cosmic-ray detector based on a deep three-dimensional electromagnetic calorimeter, proposed to be...

    Go to contribution page
  7. 11. Virtual Painting recoloring using Vision Transformer on Deep Embedded X-Ray Fluoresce synthetic dataset
    Alessandro Bombini (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 17:10

    In the last few years, the rise of deep learning techniques has affected also the field on physics-based imaging applied to cultural heritage. One possible application of such techniques is the virtual digital restoration of pictorial artworks.

    Two main problems we face when exploring such landscape are

    1. The small dataset sizes (due to the slow pace of such analysis, as well as...
    Go to contribution page
  8. 12. First Stages on Spectral Classification using Synthetic Datasets.
    Fernando Garcia-Avello Bofias (Istituto Nazionale di Fisica Nucleare)
    11/06/2024, 17:35

    X-ray fluorescence (XRF) has been extensively utilized across various disciplines for an extended period. Despite the long-standing availability of fundamental physical parameters associated with the process, the extraction of elemental information from spectra remains
    predominantly a manual or algorithmic endeavor, given the spectral variations and inherent complexity in different fields of...

    Go to contribution page
  9. 5. AI-based approach for provider selection in the INDIGO PaaS Orchestration System of INFN Cloud
    Luca Giommi (Istituto Nazionale di Fisica Nucleare)
    12/06/2024, 09:15

    INFN Cloud provides scientific communities supported by the Institute with a federated Cloud infrastructure and a dynamic portfolio of services based on the needs of the supported use cases. The federative middleware of INFN Cloud is based on the INDIGO PaaS orchestration system, consisting of interconnected open-source microservices. Among these, the INDIGO PaaS Orchestrator receives...

    Go to contribution page
  10. 16. Transformer-based models for scientific text classification
    Giovanni Zurlo (Università di Giovanni)
    12/06/2024, 09:40

    The transformer model, introduced by Google in 2017, has become renowned in natural language processing (NLP). It represents a significant advancement completely departing from the mechanisms of Recurrent Neural Networks and Convolutional Neural Networks.
    The features that contribute to the superior performance of transformers in NLP tasks include self-attention, multi-head attention, and...

    Go to contribution page
  11. 15. Leveraging RAG Architecture for Effective Email Response Automation: a CNAF Tier-1 User Support use case
    Alberto Trashaj (Università di Bologna)
    12/06/2024, 10:05

    CNAF provides computing resources to over 60 scientific communities and supports over 1700 active users through its User Support (US) department. US handles daily emails and tickets to help users in employing effectively computing resources and using latest software technologies. Since 2003, CNAF hosts the main INFN computing center, one of WLCG Tier-1.

    The primary challenge is to handle...

    Go to contribution page
  12. 7. Multi-scale cross attention transformer encoder for $\tau$ lepton pair invariant mass reconstruction
    Valentina Camagni (Universita & INFN, Milano-Bicocca (IT))
    12/06/2024, 11:00

    With the observation of the Standard Model Higgs boson (H) by the CMS and ATLAS experiments in 2012, the last missing elementary particle predicted by the Standard Model of particle physics was found. Since then, extensive measurements in various decay channels of the Higgs boson have been performed. One of them is the decay into a pair of $\tau$ leptons. It is the decay channel of the Higgs...

    Go to contribution page
  13. 6. Hyperparameter Optimization for Deep Learning Models Using High Performance Computing
    Muhammad Numan Anwar (Politecnico di Bari and Istituto Nazionale di Fisica Nucleare Bari, Italy)
    12/06/2024, 11:25

    Clusters counting in a drift chamber represents the most promising breakthrough in particle identification (PID) techniques in particle physics experiments. In this paper, neural network models, such as the Long Short-Term Memory (LSTM) Model and Convolutional Neural Network (CNN) Model, are trained using various hyperparameters like loss functions, activation functions, different numbers of...

    Go to contribution page
  14. 10. Quantum Machine learning frameworks for charged particle tracking
    Laura Cappelli (Istituto Nazionale di Fisica Nucleare)
    12/06/2024, 11:50

    With the advent of the High Luminosity LHC era, which is expected to significantly increase the amount of data collected by the detectors, the computational complexity of the particle tracking problem is expected to increase.

    Conventional algorithms suffer from scaling problems. In our work, we represent charged particle tracks as a graph data structure and we are investigating the use of...

    Go to contribution page
  15. 3. Final remarks and closing
    Elisabetta Ronchieri (Istituto Nazionale di Fisica Nucleare)
    12/06/2024, 12:15