Abstract: Selecting an appropriate step size is critical in Gradient Descent algorithms used to train Neural Networks for Deep Learning tasks. A small value of the step size leads to slow convergence, ...

In autonomous driving, understanding the 3D world over time is critical. Yet, most vision-based 3D Occupancy (VisionOcc) methods only scratch the surface of temporal fusion, focusing on simple ...

Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...

Abstract: In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-task learning (MTL) models in motor imagery (MI)-based ...

State-of-the-art techniques for pavement performance evaluation have attracted considerable attention in recent years. Artificial Neural Networks (ANNs) can simulate the human brain to discover hidden ...

The Buddhist monks are up and ready early Saturday morning as they make their "Walk For Peace" toward the North Carolina State Capitol. They spent the night at Apex High School. The Buddhist monks are ...