Deep Transfer Learning for Industrial Automation: A Review and Discussion of New Techniques for Data-Driven Machine Learning

6 December 2020

Papers citing "Deep Transfer Learning for Industrial Automation: A Review and Discussion of New Techniques for Data-Driven Machine Learning"

6 / 6 papers shown

Title
Human-inspired Explanations for Vision Transformers and Convolutional Neural Networks Mahadev Prasad Panda Matteo Tiezzi Martina Vilas Gemma Roig Bjoern M. Eskofier Dario Zanca ViT AAML 41 1 0 04 Aug 2024
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions Peng Yan Ahmed Abdulkadir Paul-Philipp Luley Matthias Rosenthal Gerrit A. Schatte Benjamin Grewe Thilo Stadelmann AI4TS 36 59 0 11 Jul 2023
Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challenges K. T. Baghaei Amirreza Payandeh Pooya Fayyazsanavi Shahram Rahimi Zhiqian Chen Somayeh Bakhtiari Ramezani FaML AI4TS 38 6 0 27 Nov 2022
Enhancing an Intelligent Digital Twin with a Self-organized Reconfiguration Management based on Adaptive Process Models Timo Müller Benjamin Lindemann Tobias Jung N. Jazdi M. Weyrich AI4CE 19 19 0 07 Jul 2021
Regularization-based Continual Learning for Anomaly Detection in Discrete Manufacturing Benjamin Maschler T. Pham M. Weyrich 43 32 0 02 Jan 2021
Transfer Learning as an Enabler of the Intelligent Digital Twin Benjamin Maschler Dominik I. Braun N. Jazdi M. Weyrich AI4CE 26 39 0 03 Dec 2020