Mirror u-net: Marrying multimodal fission with multi-task learning for semantic segmentation in medical imaging
Abstract Positron Emission Tomography (PET) and Computed Tomography (CT) are
routinely used together to detect tumors. PET/CT segmentation models can automate tumor …
routinely used together to detect tumors. PET/CT segmentation models can automate tumor …
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments
Deep learning-based models are at the top of most driver observation benchmarks due to
their remarkable accuracies but come with a high computational cost, while the resources …
their remarkable accuracies but come with a high computational cost, while the resources …
SynthAct: Towards Generalizable Human Action Recognition based on Synthetic Data
Synthetic data generation is a proven method for augmenting training sets without the need
for extensive setups, yet its application in human activity recognition is underexplored. This …
for extensive setups, yet its application in human activity recognition is underexplored. This …
Minimizing Gaps Between Synthetic And Real Datasets
M Zhang - 2023 - research-collection.ethz.ch
Creating synthetic images that are of high quality is a crucial step for many deep learning
projects, especially when real data are either limited or too expensive to acquire. Despite its …
projects, especially when real data are either limited or too expensive to acquire. Despite its …