Although deep learning has achieved satisfactory performance in computer vision, a large
volume of images is required. However, collecting images is often expensive and …

The object detection in aerial images is one of the most commonly used tasks in the wide-
range of computer vision applications. However, the object detection is more challenging …

Object detection accuracy on small objects, ie, objects under 32× 32 pixels, lags behind that
of large ones. To address this issue, innovative architectures have been designed and new …

The development of object detection has led to huge improvements in human interaction
systems. Object detection is a challenging task because it involves many parameters …

Object detection is the most important problem in computer vision tasks. After AlexNet
proposed, based on Convolutional Neural Network (CNN) methods have become …

Colorectal cancer (CRC) is one of the most common types of cancer with a high mortality
rate. Colonoscopy is the preferred procedure for CRC screening and has proven to be …

As one type of object detection, small object detection has been widely used in daily-life-
related applications with many real-time requirements, such as autopilot and navigation …

Automated driving and vehicle safety systems need object detection. It is important that
object detection be accurate overall and robust to weather and environmental conditions …

Limited by the size, location, number of samples and other factors of the small object itself,
the small object is usually insufficient, which degrades the performance of the small object …

Due to the difficulty in acquiring massive task-specific occluded images, the classification of
occluded images with deep convolutional neural networks (CNNs) remains highly …