FOSNet fuses object and scene features via CNN and uses scene coherence loss to report SOTA accuracies of 60.14% on Places2 and 90.37% on MIT Indoor67.
Support-vector networks,
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HuBERT reaches 86% accuracy and 0.93 AUC detecting COVID-19 from 893 voice samples in the Cambridge COVID-19 Sound database.
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FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition
FOSNet fuses object and scene features via CNN and uses scene coherence loss to report SOTA accuracies of 60.14% on Places2 and 90.37% on MIT Indoor67.
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Developing a Multi-variate Prediction Model For COVID-19 From Crowd-sourced Respiratory Voice Data
HuBERT reaches 86% accuracy and 0.93 AUC detecting COVID-19 from 893 voice samples in the Cambridge COVID-19 Sound database.