HexNet: An Orientation-Aware Deep Learning Framework for Omni-Directional Input
While omni-directional sensors provide holistic representations typical deep learning
frameworks reduce the benefits by introducing distortions and discontinuities as spherical …
frameworks reduce the benefits by introducing distortions and discontinuities as spherical …
Quantifying U‐Net uncertainty in multi‐parametric MRI‐based glioma segmentation by spherical image projection
Background Uncertainty quantification in deep learning is an important research topic. For
medical image segmentation, the uncertainty measurements are usually reported as the …
medical image segmentation, the uncertainty measurements are usually reported as the …
Rotation equivariant orientation estimation for omnidirectional localization
Deep learning for 6-degree-of-freedom (6-DoF) camera pose estimation is highly efficient at
test time and can achieve accurate results in challenging, weakly textured environments …
test time and can achieve accurate results in challenging, weakly textured environments …
Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction
Purpose To develop a novel deep ensemble learning model for accurate prediction of brain
metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). Methods and …
metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). Methods and …
Real-Time Semantic Segmentation of Spherical Images for Automotive Applications
Recent advancements in autonomous driving technology have resulted in a growing need
for robust algorithms that can effectively detect, recognize, and segment objects in the …
for robust algorithms that can effectively detect, recognize, and segment objects in the …