Object detection and recognition are an integral part of computer vision systems. In computer vision, the work begins with a breakdown of the scene into components that a computer can see and analyse.

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications.

In this article, we will discuss how to apply computer vision technology ... finding objects in space is not enough. We have to identify the type of object (Object Detection), as well as how ...

Then it sends the data through a transformer encoding and decoding process. Finally, the data will go to a shared feed-forward network (FFN) that predicts an object detection or a ... architectures ...

Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

Learn More Computer Vision (CV) has evolved rapidly in recent ... solve certain CV problems extremely well. Challenges like object detection and classification were especially ripe for the deep ...

At the Google Cloud Next conference, Google introduced a new computer vision platform, Vertex AI Vision, that simplifies the process of building analytics based on live camera streams and videos.

Earlier this week Google announced its MobileNets family of lightweight computer vision models. These models can handle tasks like object detection, facial recognition and landmark recognition.