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cs.LG2024
An Early-Stage Workflow Proposal for the Generation of Safe and Dependable AI Classifiers
Hans Dermot Doran, Suzana Veljanovska
The generation and execution of qualifiable safe and dependable AI models, necessitates definition of a transparent, complete yet adaptable and preferably lightweight workflow. Giv…
cs.CV2024
Performance Examination of Symbolic Aggregate Approximation in IoT Applications
Suzana Veljanovska, Hans Dermot Doran
Symbolic Aggregate approXimation (SAX) is a common dimensionality reduction approach for time-series data which has been employed in a variety of domains, including classification…
cs.AI2024
Hybrid Convolutional Neural Networks with Reliability Guarantee
Hans Dermot Doran, Suzana Veljanovska
Making AI safe and dependable requires the generation of dependable models and dependable execution of those models. We propose redundant execution as a well-known technique that c…