This study explores the effectiveness of Explainable Artificial Intelligence (XAI) for predicting
suicide risk from medical tabular data. Given the common challenge of limited datasets in …

Deep learning models have significantly improved object detection, which is essential for
visual sensing. However, their increasing complexity results in higher latency and resource …

Real-time detection of workers is crucial in construction safety management. Deep learning-
based detecting methods are valuable, but always challenged by the possibility of target …

Multi-modal fusion methods combine the advantages of both point clouds and RGB images
to boost the performance of 3D object detection. Despite the significant progress, we find …

Lightweight detection methods are frequently utilized for unmanned system sensing;
however, to tackle the challenge of low precision in detecting small targets on the water's …

In object detection, Transformer-based models such as DETR have exhibited state-of-the-art
performance, capitalizing on the attention mechanism to handle spatial relations and feature …

In the field of medical image analysis, object detection plays a crucial role by providing
interpretable diagnostic information to healthcare professionals. Although current object …

Successfully detecting small pedestrians through vehicle camera sensors would greatly
facilitate the development of autonomous driving safety applications. However, the existing …

In the context of 3C assembly scenarios, characterized by numerous semi-flexible,
heterogeneous, and small slender targets, traditional target detection algorithms face …

In order to solve the superimposed image distortion caused by explosion shock wave and
shooting tilt in warhead explosion test, and the problem of small target of the fragment …