Abstract: Traditional deep learning methods have achieved remarkable success by leveraging large-scale labeled datasets. However, in real-world applications, acquiring labeled data is often expensive, ...
ABSTRACT: Under variable-speed conditions in modern industry, rolling bearing vibration signals are highly non-stationary, and fault features are easily obscured by speed interference and noise.
Abstract: Utilizing multi-view infrared images to collaboratively identify the types of surface ship targets is a feasible approach in practice. This paper proposes a fine-grained object recognition ...
This project presents a deep learning–based image processing system for enhancing ultrasound images by suppressing speckle noise and tissue clutter while preserving anatomical structures.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results