Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …

After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …

The effectiveness of Object Detection, one of the central problems in computer vision tasks,
highly depends on the definition of the loss function-a measure of how accurately your ML …

Object detection is a significant downstream task in computer vision. For the on-board edge
computing platforms, a giant model is difficult to achieve the real-time detection requirement …

Defect detection is the most important step in the postpartum reprocessing of kiwifruit.
However, there are some small defects difficult to detect. The accuracy and speed of existing …

To solve the problems of low accuracy, low real-time performance, poor robustness and
others caused by the complex environment, this paper proposes a face mask recognition …

To solve object detection issues in infrared images, such as a low recognition rate and a
high false alarm rate caused by long distances, weak energy, and low resolution, we …

Hospital emergency departments frequently receive lots of bone fracture cases, with
pediatric wrist trauma fracture accounting for the majority of them. Before pediatric surgeons …

Abstract Knowledge distillation (KD) has witnessed its powerful capability in learning
compact models in object detection. Previous KD methods for object detection mostly focus …

In real life, object detection is widely applied and plays a significant part in the field of
computer vision. However, when detecting small objects, the advanced You Only Look Once …