Recently, machine/deep learning techniques are achieving remarkable success in a variety
of intelligent control and management systems, promising to change the future of artificial …

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 …

In recommender systems, users' behavior data are driven by the interactions of user-item
latent factors. To improve recommendation effectiveness and robustness, recent advances …

Navigating safely and dependably through challenging weather conditions poses a
significant hurdle for autonomous vehicles (AVs). While state-of-the-art object detection …

Causal structure learning, a prominent technique for encoding cause and effect
relationships among variables, through Bayesian Networks (BNs). Merely recovering causal …

Due to its insensitivity to light intensity and the capability to capture multidimensional
information, polarimetric imaging technology has been proven to have advantages over …

Few-shot hyperspectral image (HSI) classification poses challenges due to sample selection
bias in few-shot scenarios, potentially leading to incorrect statistical associations between …

Despite the success of deep learning-based object detection methods in recent years, it is
still challenging to make the object detector reliable in adverse weather conditions such as …

Clothes-invariant feature extraction is critical to the clothes-changing person re-identification
(CC-ReID). It can provide discriminative identity features and eliminate the negative effects …

Computer vision is now vital in intelligent vehicle environment perception systems. However,
real-time small-scale pedestrian detection in intelligent vehicle environment perception …