Intelligent fault diagnosis achieves tremendous success in machine fault diagnosis because
of its outstanding data-driven capability. However, the severely imbalanced dataset in …

Conventional knowledge graphs (KGs) are composed solely of entities, attributes, and
relationships, which poses challenges for enhancing multimodal knowledge representation …

Abstract World Health Organization (WHO) records that skin cancer has vigorously affected
people in recent decades. Worldwide, many people are affected by skin cancer, and its …

Abstract Data-Free Knowledge Distillation (DFKD) can be used to train students using
synthetic data, when the original dataset of the teacher network is not accessible. However …

With the rapid development of artificial intelligence and the Internet of Things technology, the
automatic music composition system has become a hot topic of research. This paper …

In this work we address the data privacy concerns and the need of extensive data sets by the
deep learning models. We account the need of low computational frame work along with …

When a laser carrying image information is transmitted in seawater, the presence of ocean
turbulence leads to significant degradation of the received information due to the effect of …

The increasing trend in deep generative modelling, which offers data scarcity and diversity
solutions in machine learning, is one of the most recent developments in the field. The data …

In these last years, communication with computers has made enormous steps, like the robot
Sophia that surprised many people with their human interactions, behind this kind of robot …

自然科学和社会科学领域内的控制系统往往表现出很强的非线性行为且被控对象往往与多个
输入项相关, 因此, 对其系统的参数辨识更加困难. 本文提出了一种基于改进生成对抗网络的参数 …