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Ontologies in modelling and analysing of big genetic data
Published 2025-01-01“…One of the main problems of deep learning is the lack of interpretability, since neural networks often function as “black boxes” unable to explain their decisions. This paper describes approaches to creating methods for interpreting deep learning models and presents two examples of self-explanatory ontology-based deep learning models: (1) Deep GONet, which integrates Gene Ontology into a hierarchical neural network architecture, where each neuron represents a biological function. …”
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Investigations on the Hot Stamping of AW-7921-T4 Alloy Sheet
Published 2017-01-01Get full text
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Multifrequency Piezoelectric Energy Harvester Based on Polygon-Shaped Cantilever Array
Published 2018-01-01Get full text
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A dataset of annotated African plum images from Cameroon for AI-based quality assessmentKaggle
Published 2025-04-01Get full text
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Analytical Solutions of Fractional Walter’s B Fluid with Applications
Published 2018-01-01Get full text
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Photodegradation of Eosin Y Using Silver-Doped Magnetic Nanoparticles
Published 2015-01-01Get full text
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