Neural Network Architectures
Neural Network Architectures is a branch of Artificial Intelligence Algorithms that deals with the design and implementation of neural networks, which are computational models inspired by the structure and function of biological neurons. These architectures can be used for various tasks in image processing such as object detection, recognition, and segmentation. They consist of interconnected nodes or artificial neurons arranged in layers, where each node performs a simple computation on its inputs and passes the result to the next layer. The connections between nodes have associated weights that are adjusted during training to optimize the network's performance. Common types of neural network architectures include feedforward networks, recurrent networks, convolutional neural networks (CNNs), and deep belief networks (DBNs). These architectures can be combined and customized to suit specific image processing tasks, making them a powerful tool for addressing complex problems in this field.