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Results 1-18 of 41
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Seed project:Automated Assembly/Disassembly Instructions (ADDITION) The project aims at building a consortium interested in laying the foundation for harnessing the power of AI and digitalization for…
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Project: In-line visual inspection using unsupervised learning The purpose of this project is to introduce and improve machine learning- assessment of the quality of massproduced industrial (steel)…
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The Linnaeus region continues to invest in strengthening small companies with SEK 13.7 million to new IoT project News
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Seed project: IoT for ships – an untapped data resource The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is to establish…
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New doctoral thesis on how to engineer intelligent, AI-based systems News
- Mauro Caporuscio Professor
- +46 470-70 85 58
- maurocaporusciolnuse
- Nadeem Abbas Senior lecturer
- +46 470-76 74 11
- nadeemabbaslnuse
- Gaurav Garg
- gauravgarglnuse
- Keegan Mbiyana Doctoral student
- +46 470-70 82 09
- +46 70-309 54 22
- keeganmbiyanalnuse
- Janka Kovacikova Senior lecturer
- +46 470-70 80 91
- jankakovacikovalnuse
- Ares Argelia Gomez Gallegos Associate senior lecturer
- +46 470-70 80 25
- aresgomezlnuse
- Jetro Kenneth Pocorni Senior lecturer
- +46 470-76 72 01
- +46 70-261 55 43
- jetropocornilnuse
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New research on Data-driven Fault Diagnosis for Cyber-Physical Systems News
- Daniel Nilsson
- danielfnilssonlnuse
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Doctoral project: Realising smarter organization by developing Digital Twin of the Organization A Digital Twin of an Organization (DTO) as a software component proposes a live model of an…
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Project: Smart Dat The goal of the project is to offer activities in automation and digitalization for small and medium-sized companies in the manufacturing sector in the Linnaeus region, strengthen…
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Doctoral project: Application of AI in the software development process This project aims to streamline the software system development process by leveraging AI.
- Rammohan Kodakadath Premachandran Doctoral student
- +46 470-70 83 31
- rammohanpremachandranlnuse