Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

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 …

Benefiting from the development of convolutional neural networks (CNNs), many excellent
algorithms for object detection have been presented. Remote sensing object detection …

In the past years, the computer vision domain has been profoundly changed by the advent of
deep learning algorithms and data science. The defect detection problem is of outmost …

The" shared head for classification and localization"(sibling head), firstly denominated in
Fast RCNN, has been leading the fashion of the object detection community in the past five …

Compared with model architectures, the training process, which is also crucial to the
success of detectors, has received relatively less attention in object detection. In this work …

Current state-of-the-art detectors typically exploit feature pyramid to detect objects at
different scales. Among them, FPN is one of the representative works that build a feature …

The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

The way that information propagates in neural networks is of great importance. In this paper,
we propose Path Aggregation Network (PANet) aiming at boosting information flow in …