Deep learning relies on learning from extensive data to generate prediction results. This
approach may inadvertently capture spurious correlations within the data, leading to models …

Deep learning has revolutionized the field of artificial intelligence. Based on the statistical
correlations uncovered by deep learning-based methods, computer vision tasks, such as …

The goal of video summarization is to automatically shorten videos such that it conveys the
overall story without losing relevant information. In many application scenarios, improper …

Causal reasoning is viewed as crucial for achieving human-level machine intelligence.
Recent advances in language models have expanded the horizons of artificial intelligence …

Outlier detection (outlier and anomaly are used interchangeably in this review) in non-
independent and identically distributed (non-IID) data refers to identifying unusual or …

Medical image diagnosis has developed rapidly under the impetus of the deep network.
Previous works mainly focus on improving the diagnostic accuracy of models, ie, first use a …

Geometric shape features have been widely used as strong predictors for image
classification. Nevertheless, most existing classifiers such as deep neural networks (DNNs) …

Image denoising techniques are pivotal in preprocessing noisy images, greatly enhancing
the quality of visual data in applications within the realm of Cyber-Physical Systems (CPS) …

Deep learning heavily relies on statistical correlations to drive artificial intelligence (AI)
innovations, particularly in computer vision applications like autonomous driving and …

Abstract Flexible Printed Circuit (FPC) is a highly space-efficient and flexible circuit board.
Integrating object detection technology into the FPC production process facilitates …