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Found 6 papers, 1 papers with code
Sepsis Prediction and Vital Signs Ranking in Intensive Care Unit Patients
For the detection of sepsis, severe sepsis, and septic shock, our model achieves an AUC of 0. 97, 0. 96 and 0. 91, respectively.
Pathology Extraction from Chest X-Ray Radiology Reports: A Performance Study
Our results demonstrate the inadequacy of generic APIs for pathology extraction task and establish the importance of domain specific model training for improved results.
Abnormality Detection and Localization in Chest X-Rays using Deep Convolutional Neural Networks
One remarkable result of the cardiomegaly localization is that the heart and its surrounding region is most responsible for cardiomegaly detection, in contrast to the rule based models where the ratio of heart and lung area is used as the measure.
Shallow Networks for High-Accuracy Road Object-Detection
The ability to automatically detect other vehicles on the road is vital to the safety of partially-autonomous and fully-autonomous vehicles.
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
(2) Smaller DNNs require less bandwidth to export a new model from the cloud to an autonomous car.
Ranked #1 on
Image Classification
on ImageNet-P
FireCaffe: near-linear acceleration of deep neural network training on compute clusters
Therefore, the key consideration here is to reduce communication overhead wherever possible, while not degrading the accuracy of the DNN models that we train.
Ranked #1032 on
Image Classification
on ImageNet
