Knowledge Probabilization in Ensemble Distillation: Improving Accuracy and Uncertainty Quantification for Object Detectors

Information Science, Computer Science, Artificial Intelligence,
knowledge probabilization   ensemble distillation   object detection   uncertainty quantification   deep neural networks   accuracy improvement   feature knowledge  

Research on the Application of Knowledge Probabilization in Ensemble Distillation Academic Background: Significance of the Research and Problem Statement In recent years, deep neural networks (DNNs) have found broad applications in safety-critical fields such as autonomous driving, medical diagnosis, and climate prediction due to their outstanding ...

Heuristic Underwater Perceptual Enhancement with Semantic Collaborative Learning

Engineering, Ocean Engineering, Information Science, Computer Science, Artificial Intelligence,
underwater image enhancement   deep learning   color correlation   object detection   semantic collaborative learning   invertible network   heuristic prior  

Academic Background and Problem Statement Underwater images have significant application value in fields such as marine exploration, underwater robotics, and marine life identification. However, due to the refraction and absorption of light by water, underwater images often suffer from low contrast and color distortion, which severely impacts the a...

Enhancing Fall Risk Assessment: Instrumenting Vision with Deep Learning During Walks

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Bioengineering,
fall risk   gait analysis   object detection   deep learning   visual attention  

Introduction Fall events are common across various clinical populations, with usual risk assessments including visual observation of individual gait. However, gait observation assessments are typically confined to laboratory settings, involving standardized walking protocol tests to identify potential defects that might increase fall risk. Subtle d...