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: 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.
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 ...
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: 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 ...
TRAM: Transformer-Based Mask R-CNN Framework for Underwater Object Detection in Side-Scan Sonar Data
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: Domain Adaptation (DA) is of critical importance in practical remote sensing object detection, aiming to address the performance degradation caused by significant domain discrepancies ...
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