6.5k citations · 6.6k across the 4 of their papers we have counts for
6 papers
Pathology Extraction from Chest X-Ray Radiology Reports: A Performance Study
Tahsin Mostafiz, Khalid Ashraf
Extraction of relevant pathological terms from radiology reports is important for correct image label generation and disease population studies. In this letter, we compare the perf…
Sepsis Prediction and Vital Signs Ranking in Intensive Care Unit Patients
Avijit Mitra, Khalid Ashraf
We study multiple rule-based and machine learning (ML) models for sepsis detection. We report the first neural network detection and prediction results on three categories of sepsi…
Abnormality Detection and Localization in Chest X-Rays using Deep Convolutional Neural Networks
Mohammad Tariqul Islam, Md Abdul Aowal, Ahmed Tahseen Minhaz +1
Chest X-Rays (CXRs) are widely used for diagnosing abnormalities in the heart and lung area. Automatically detecting these abnormalities with high accuracy could greatly enhance re…
Shallow Networks for High-Accuracy Road Object-Detection
Khalid Ashraf, Bichen Wu, Forrest N. Iandola +2
The ability to automatically detect other vehicles on the road is vital to the safety of partially-autonomous and fully-autonomous vehicles. Most of the high-accuracy techniques fo…
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Forrest N. Iandola, Song Han, Matthew W. Moskewicz +3
Recent research on deep neural networks has focused primarily on improving accuracy. For a given accuracy level, it is typically possible to identify multiple DNN architectures tha…
FireCaffe: near-linear acceleration of deep neural network training on compute clusters
Forrest N. Iandola, Khalid Ashraf, Matthew W. Moskewicz +1
Long training times for high-accuracy deep neural networks (DNNs) impede research into new DNN architectures and slow the development of high-accuracy DNNs. In this paper we presen…