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1. |
Record Nr. |
UNINA990009791870403321 |
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Autore |
De Seta, Cesare <1941- > |
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Titolo |
I ritratti e i paesaggi di Lalla Romano tra iconografia e testo letterario / Cesare De Seta |
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Pubbl/distr/stampa |
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Roma : Edizioni Sintesi informazione, 1999 |
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Descrizione fisica |
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Locazione |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Estratto da: Arte d'Occidente : temi e metodi : studi in onore di Angiola Maria Romanini |
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2. |
Record Nr. |
UNISA990002579370203316 |
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Autore |
DE ANGELIS, Giovanna |
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Titolo |
Il pensiero di j.o. de la mettrie / De Angelis Giovanna ; relatore Alfredo Sabetti |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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3. |
Record Nr. |
UNINA9910869168203321 |
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Autore |
Wagner Achim |
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Titolo |
Advances in Artificial Intelligence in Manufacturing : Proceedings of the 1st European Symposium on Artificial Intelligence in Manufacturing, September 19, 2023, Kaiserslautern, Germany / / edited by Achim Wagner, Kosmas Alexopoulos, Sotiris Makris |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (207 pages) |
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Collana |
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Lecture Notes in Mechanical Engineering, , 2195-4364 |
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Altri autori (Persone) |
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AlexopoulosKosmas |
MakrisSotiris |
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Disciplina |
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Soggetti |
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Automation |
Industrial engineering |
Production engineering |
Human-machine systems |
Industrial and Production Engineering |
Human-Machine Interfaces |
Process Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- Organization -- Contents -- Artificial Intelligence at Manufacturing System Level -- An Integrated Active Learning Framework for the Deployment of Machine Learning Models for Defect Detection in Manufacturing Environments -- 1 Introduction -- 2 The Problem -- 2.1 Active Learning -- 2.2 Deployment -- 2.3 Monitoring -- 2.4 Explainability -- 3 Use Cases -- 3.1 Binary Classification -- 3.2 Multiclass Classification -- 3.3 Object Detection -- 4 Results -- 4.1 Binary Classification -- 4.2 Multiclass Classification -- 4.3 Object Detection -- 4.4 MLOps -- 5 Conclusions -- 6 Aknowlegments -- References -- Complex and Big Data Handling and Monitoring Through Machine Learning Towards Digital-Twin in High Precision Manufacturing -- 1 Introduction -- 2 Brief Overview of the State-of-the-Art -- 3 Real Case Studies -- 4 Proposed Methods -- 4.1 Low-Dimensional Learning for Machine Health Condition Monitoring -- 4.2 Recurrent NNs for Multi-stream Process Pattern Prediction |
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Sommario/riassunto |
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This book reports on recent developments of artificial intelligence applications in the manufacturing industry. Gathering contributions to the first European Symposium on Artificial Intelligence in Manufacturing, held on September 19, 2023, in Kaiserslautern, Germany, it reports on machine learning models and algorithms for systems monitoring and industrial data management, on advances in human-robot collaboration, and on artificial intelligence applications in industrial control and process monitoring. Giving a special emphasis to the integration of artificial intelligence in manufacturing systems and processes, this book offers a timely and practice-oriented guide to a multidisciplinary audience of engineering researchers, software developers and industrial managers. |
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