objektigenkänningsnätverk
An object recognition network, often abbreviated as ORN, is a type of artificial neural network designed to identify and classify objects within digital images or videos. These networks are a subset of convolutional neural networks (CNNs), which are specifically engineered to process and analyze visual data. The primary goal of an ORN is to accurately detect and recognize objects by learning from large datasets of labeled images.
The architecture of an ORN typically includes several key components. The first layer, known as the convolutional
Training an ORN involves a process called backpropagation, where the network adjusts its internal parameters to
Object recognition networks have a wide range of applications, including autonomous vehicles, robotics, surveillance systems, and