Empirical evaluation of CNNs for facial expression recognition shows that models trained on non-ID data do not transfer to individuals with intellectual disabilities, requiring user-specific training.
Xception: Deep learning with depthwise separable convolu- tions
2 Pith papers cite this work. Polarity classification is still indexing.
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Deep learning systems for glacier calving front delineation in SAR imagery exhibit errors up to 221 m while human annotators deviate by only 38 m.
citing papers explorer
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Assessing the Efficacy of Deep Learning Approaches for Facial Expression Recognition in Individuals with Intellectual Disabilities
Empirical evaluation of CNNs for facial expression recognition shows that models trained on non-ID data do not transfer to individuals with intellectual disabilities, requiring user-specific training.
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Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning
Deep learning systems for glacier calving front delineation in SAR imagery exhibit errors up to 221 m while human annotators deviate by only 38 m.