The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to
be a crucial process in many applications, such as in autonomous driving, industrial …

Object detection of optical remote sensing image is an important and challenging problem.
And it is widely used in the field of aerial and satellite image analysis. With the rapid …

When training an anchor-based object detector with a sparsely annotated dataset, the effort
required to locate positive examples can cause performance degradation. Because anchor …

Abstract Recently, Convolutional Neural Networks (CNNs) have achieved great success in
object detection due to their outstanding abilities of learning powerful features on large …

We exploit the computational capability of deep convolutional neural network (CNN)
architecture and the natural interpretability of the co-occurrence matrix (CM) to learn deep co …

Weakly-supervised object detection attempts to limit the amount of supervision by
dispensing the need for bounding boxes, but still assumes image-level labels on the entire …

The automated recognition of surgical instruments in surgical videos is an essential factor for
the evaluation and analysis of surgery. The analysis of surgical instrument localization …

With the growing advances in deep learning based technologies the detection and
identification of co-occurring objects is a challenging task which has many applications in …