Deep Learning has become exceptionally popular in the last few years due to its success in
computer vision [1–3] and other fields of AI [4–6]. However, deep neural networks are …

With the emergence of onboard vision processing for areas such as the internet of things
(IoT), edge computing and autonomous robots, there is increasing demand for …

Object detection techniques that achieve state-of-the-art detection accuracy employ
convolutional neural networks, implemented to have lower latency in graphics processing …

This work presents a study for building a Deep Vision pipeline suitable for the Robocup
Standard Platform League, a humanoid robot soccer tournament. Specifically, we focus on …

RoboCup is one of the major global AI events, gathering hundreds of teams from the world's
best universities to compete in various tasks ranging from soccer to home assistance and …

In most applications for autonomous robots, the detection of objects in their environment is of
significant importance. As many robots are equipped with cameras, this task is often solved …

The essential part in developing the humanoid robot which is able to play soccer is the
vision system. The vision system needs to be fast and accurate in detecting the surrounding …

Object detection remains an active area of research in the field of computer vision, and
considerable advances and successes has been achieved in this area through the design of …

Vision-based object detection is essential for a multitude of robotic applications. However, it
is also a challenging job due to the diversity of the environments in which such applications …

In this paper, we consider the task of detecting the players and sports balls in real-world
handball images, as a building block for action recognition. Detecting the ball is still a …