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Contextgpt: Infusing llms knowledge into neuro-symbolic activity recognition models
Context-aware Human Activity Recognition (HAR) is a hot research area in mobile
computing, and the most effective solutions in the literature are based on supervised deep …
computing, and the most effective solutions in the literature are based on supervised deep …
Neuro-Symbolic AI: Explainability, Challenges, and Future Trends
X Zhang, VS Sheng - arxiv preprint arxiv:2411.04383, 2024 - arxiv.org
Explainability is an essential reason limiting the application of neural networks in many vital
fields. Although neuro-symbolic AI hopes to enhance the overall explainability by leveraging …
fields. Although neuro-symbolic AI hopes to enhance the overall explainability by leveraging …
Activity Recognition within a Manufacturing System: A Comparison of Logic Programming, Machine Learning, and Combinatorial Optimization Based Methods
A systematic investigation of machine learning and``domain knowledge''based Activity
Recognition (AR) methods was undertaken for a manufacturing based used case involving …
Recognition (AR) methods was undertaken for a manufacturing based used case involving …