Object Detection is the task of classification and localization of objects in an image or video.
It has gained prominence in recent years due to its widespread applications. This article …

This work explores and compares the plethora of metrics for the performance evaluation of
object-detection algorithms. Average precision (AP), for instance, is a popular metric for …

In he past decade, object detection has achieved significant progress in natural images but
not in aerial images, due to the massive variations in the scale and orientation of objects …

With the rapid development of deep learning, many deep learning-based approaches have
made great achievements in object detection tasks. It is generally known that deep learning …

Internet of Things (IoT) can help to pave the way to the circular economy and to a more
sustainable world by enabling the digitalization of many operations and processes, such as …

Augmented Reality (AR) is an augmented depiction of reality formed by overlaying digital
information on an image of objects being seen through a device. Artificial Intelligence (AI) …

Transfer learning is a widely-used paradigm in deep learning, where models pre-trained on
standard datasets can be efficiently adapted to downstream tasks. Typically, better pre …

Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …

Masonry structures represent the highest proportion of building stock worldwide. Currently,
the structural condition of such structures is predominantly manually inspected which is a …

Abstract Model efficiency has become increasingly important in computer vision. In this
paper, we systematically study neural network architecture design choices for object …