Scaling Deep Learning Research with Kubernetes on the NRP Nautilus HyperCluster
Throughout the scientific computing space, deep learning algorithms have shown excellent
performance in a wide range of applications. As these deep neural networks (DNNs) …
performance in a wide range of applications. As these deep neural networks (DNNs) …
Overhead Object Detection with Channel Attention for High-Resolution Multi-Spectral Satellite Imagery and DMP-extracted Shape Features
Deep convolutional neural networks (DCNNs) have shown excellent performance in object
detection tasks over the last five years. The widespread adoption of DCNNs in computer …
detection tasks over the last five years. The widespread adoption of DCNNs in computer …
Differential morphological profile neural network for maneuverability hazard detection in unmanned aerial system imagery
Within computer vision, deep neural networks (DNNs) have gained tremendous popularity in
recent years due to their ability to extract and classify visual features. As this technology has …
recent years due to their ability to extract and classify visual features. As this technology has …
Hybrid Differential Morphological Profile Enabled Faster R-Cnn For Object Detection In High-Resolution Remote Sensing Imagery
Deep neural network (DNN) algorithms have increased dramatically across a wide variety of
remote sensing applications. However, as computer vision (CV) researchers have utilized …
remote sensing applications. However, as computer vision (CV) researchers have utilized …
Evolutionary Learning of Differential Morphological Profile Structure for Shape Feature Enabled Faster R-CNN
Recently, computer vision tasks such as classification and object detection have been
dominated by deep neural net-work (DNN) approaches. As DNN methodologies have …
dominated by deep neural net-work (DNN) approaches. As DNN methodologies have …