Abstract: Source-Free Object Detection (SFOD) enables knowledge transfer from a source domain to an unsupervised target domain for object detection without access to source data. Most existing SFOD ...

Abstract: The aim of camouflaged object detection (COD) is to discern concealed objects within the background. Due to issues such as high similarity to the surrounding environment, small size, ...

RF-DETR is the first real-time model to exceed 60 AP on the Microsoft COCO object detection benchmark alongside competitive performance at base sizes. It also achieves state-of-the-art performance on ...

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 ...

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, ...

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 ...

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 ...