225 citations
- University of Southern DenmarkDK45 papers
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- Dwarkadas J. Sanghvi College of EngineeringIN3 papers
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- Aalto UniversityFI2 papers
- Bernstein Center for Computational Neuroscience GöttingenDE2 papers
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66 papers
Dual Model Deep Learning for Alzheimer Prognostication
Alireza Moayedikia, Sara Fin, Uffe Kock Wiil
Disease modifying therapies for Alzheimer's disease demand precise timing decisions, yet current predictive models require longitudinal observations and provide no uncertainty quan…
Multi-Agent Multimodal Large Language Model Framework for Automated Interpretation of Fuel Efficiency Analytics in Public Transportation
Zhipeng Ma, Ali Rida Bahja, Andreas Burgdorf +4
Enhancing fuel efficiency in public transportation requires the integration of complex multimodal data into interpretable, decision-relevant insights. However, traditional analytic…
Discovering Operational Patterns Using Image-Based Convolutional Clustering and Composite Evaluation: A Case Study in Foundry Melting Processes
Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Grace Ma
Industrial process monitoring increasingly relies on sensor-generated time-series data, yet the lack of labels, high variability, and operational noise make it difficult to extract…
Tailoring materials into kirigami robots
Saravana Prashanth Murali Babu, Aida Parvaresh, Ahmad Rafsanjani
Kirigami, the traditional paper-cutting craft, holds immense potential for revolutionizing robotics by providing multifunctional, lightweight, and adaptable solutions. Kirigami str…
EcBot: Data-Driven Energy Consumption Open-Source MATLAB Library for Manipulators
Juan Heredia, Christian Schlette, Mikkel Baun Kjærgaard
Existing literature proposes models for estimating the electrical power of manipulators, yet two primary limitations prevail. First, most models are predominantly tested using trad…
QAS-QTNs: Curriculum Reinforcement Learning-Driven Quantum Architecture Search for Quantum Tensor Networks
Siddhant Dutta, Nouhaila Innan, Sadok Ben Yahia +1
Quantum Architecture Search (QAS) is an emerging field aimed at automating the design of quantum circuits for optimal performance. This paper introduces a novel QAS framework emplo…