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: A crucial computer vision problem is person detection, but real-world challenges including crowded backgrounds, inconsistent lighting, and object occlusion require accurate and robust models ...
The Smart Factory AI Detection System is an AI-powered industrial monitoring solution designed to detect, count, and analyze objects in real-time using computer vision. This project simulates a smart ...
Abstract: In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of ...
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: Detecting small objects and managing occlusions remain persistent challenges in object detection tasks, particularly in complex scenarios with diverse environments or densely packed scenes.
Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment. Conventional computer-aided ...
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 ...
Abstract: Small object detection in remote sensing images is severely hampered by the significant scale variation even among small objects. Conventional methods often rely on a static receptive field ...
Abstract: Domain adaptation (DA) is of critical importance in practical remote sensing object detection, aiming to address the performance degradation caused by significant domain discrepancies ...