Abstract: Detecting distant small objects under adverse visual conditions such as rain, fog, or low light remains a critical challenge in autonomous driving. To address this issue, we propose a novel ...
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: 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: Wild forest fires pose a significant threat to ecosystems, causing habitat destruction, biodiversity loss, and severe air pollution. The rapid spread of uncontrolled fires leads to ...
Abstract: At present, mitosis detection in breast histopathology images is a critical issue for breast cancer grading. Due to the breast tissue having a complex structure, and mitosis and non-mitosis ...
Abstract: Large data volumes, dynamic scenes, and intricate object motions make video analysis extremely difficult. Traditional methods depend on human-crafted features that are not scalable. This ...
Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
Abstract: During the COVID-19 pandemic, the use of face masks became mandatory in most countries and played a critical role in reducing transmission. Even in the postpandemic era, proper mask usage ...
Abstract: Existing robotic grasp detection methods often struggle with inaccurate predictions in complex scenarios involving multiple objects and textured backgrounds. Most existing methods attempt to ...
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