Abstract: Remote sensing platforms provide crucial data for applications such as urban planning and traffic monitoring. However, detecting small objects remains challenging due to low resolution, ...

Abstract: Adverse weather conditions significantly impact the performance of autonomous driving object detection systems, leading to reduced detection accuracy and an increased false detection rate.

Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...

Abstract: Object detection in aerial imagery, particularly from unmanned aerial vehicles (UAVs) and remote sensing platforms, is crucial but faces significant challenges such as modality misalignment, ...

Abstract: Cameras and radar sensors are complementary in 3D object detection in that cameras specialize in capturing an object's visual information while radar provides spatial information and ...

Simultaneous localization and mapping (SLAM) in indoor environments remains a critical challenge, especially in GPS-denied areas where real-time Performance, low cost, and robustness are required.

Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...

Abstract: Panoramic images have been used in various applications because of their ability to provide comprehensive spatial information. However, the high cost of obtaining panoramic images and the ...

Abstract: The application of object detection in industrial transportation has witnessed substantial advancements, yielding significant enhancements in both safety and efficiency. While ...

Abstract: Aerial image object detection has gained increasing attention recently. Compared to natural scenes, this task is more challenging due to two main factors: 1) a large number of densely packed ...