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 …

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 …

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 …

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

The ability to identify objects of interest from digital visual signals is critical for many
applications of intelligent systems. For such object detection task, accuracy and …

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 …

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 paper describes a deep neural network-based detector dedicated for ball and players
detection in high resolution, long shot, video recordings of soccer matches. The detector …

The detection and localization of the ball in sport videos is crucial to better understand
events and actions occurring in those sports. Despite recent advances in the field of object …