no code implementations • 1 May 2024 • Palawat Busaranuvong, Emmanuel Agu, Deepak Kumar, Shefalika Gautam, Reza Saadati Fard, Bengisu Tulu, Diane Strong
To detect infected wounds in Diabetic Foot Ulcers (DFUs) from photographs, preventing severe complications and amputations.
no code implementations • 12 Jun 2022 • Maryam Hasan, Elke Rundensteiner, Emmanuel Agu
We also study the effect of the size of the fine-tuning dataset on the accuracy of our models.
1 code implementation • NeurIPS 2021 • Walter Gerych, Tom Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke Rundensteiner
In this work we propose Recurrent Bayesian Classifier Chains (RBCCs), which learn a Bayesian network of class dependencies and leverage this network in order to condition the prediction of child nodes only on their parents.
no code implementations • 1 Jan 2021 • Walter Gerych, Elke Rundensteiner, Emmanuel Agu
OP-DMA succeeds in mapping outliers to low probability regions in the latent space by leveraging a novel Prior-Weighted Loss (PWL) that utilizes the insight that outliers are likely to have a higher reconstruction error than inliers.
no code implementations • 25 Sep 2019 • Walter Gerych, Elke Rundensteiner, Emmanuel Agu
State-of-the-art deep learning methods for outlier detection make the assumption that anomalies will appear far away from inlier data in the latent space produced by distribution mapping deep networks.