Abstract: Small uncrewed autonmous vehicles (UAVs) equipped with deep learning models are increasingly used to detect small objects both on the ground and in aerial environments. Since small objects ...
The growing presence of trash in our water bodies highlights the urgency of removing marine debris. Autonomous underwater vehicles (AUVs) equipped with object detection capabilities can play a vital ...
Abstract: Camouflaged object detection (COD) is a challenging task that struggles to accurately detect the objects concealed in the surrounding environment. This is largely attributed to the intrinsic ...
Abstract: Unmanned aerial vehicles (UAVs) have advanced significantly and are increasingly used in civil and military field. Ensuring their safety and reliability is crucial, and fault detection is ...
Abstract: Weakly supervised object detection has emerged as a cost-effective and promising solution in remote sensing, as it requires only image-level labels and alleviates the burden of ...
Abstract: Object detection is a critical task in computer vision, with applications ranging from autonomous driving to medical imaging. Traditional object detection models, such as Fast R-CNN, have ...
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: Accurate detection and segmentation of underwater objects in side-scan sonar (SSS) imagery remain challenging due to noise, cluttered backgrounds, and low-contrast conditions. In this paper, ...
Abstract: Space noncooperative object detection (SNCOD) is an essential part of space situation awareness. The localization and segmentation capabilities of the salient object detection (SOD) method ...
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 ...
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