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"

7 / 7 papers shown

Title
HarmonE: A Self-Adaptive Approach to Architecting Sustainable MLOps Hiya Bhatt Shaunak Biswas Srinivasan Rakhunathan Karthik Vaidhyanathan AI4CE 91 0 0 19 May 2025
FovEx: Human-Inspired Explanations for Vision Transformers and Convolutional Neural Networks Mahadev Prasad Panda Matteo Tiezzi Martina G. Vilas Gemma Roig Bjoern M. Eskofier Dario Zanca ViT AAML 161 1 0 04 Aug 2024
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 95 7 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 80 19 0 07 Jul 2021
A Survey on Anomaly Detection for Technical Systems using LSTM Networks Benjamin Lindemann Benjamin Maschler N. Sahlab M. Weyrich AI4TS 101 307 0 28 May 2021
Regularization-based Continual Learning for Anomaly Detection in Discrete Manufacturing Benjamin Maschler T. Pham M. Weyrich 132 37 0 02 Jan 2021
Transfer Learning as an Enabler of the Intelligent Digital Twin Benjamin Maschler Dominik I. Braun N. Jazdi M. Weyrich AI4CE 72 40 0 03 Dec 2020