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: Fine-grained object detection (FOD) is essential in many remote sensing image interpretation tasks. Existing FOD methods have achieved remarkable progress in modeling discriminative features ...
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: 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, ...
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