Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that analyze and learn features from large amounts of data. CNNs are a subset of machine learning and are a core part of deep learning algorithms. They are especially useful for finding patterns in images to recognize objects, classes, and categories.
The image depicts the architecture of a CNN, showing how it processes data through multiple layers including convolutional layers, pooling layers, and fully connected layers. The second image demonstrates the application of CNNs in image recognition, where the network learns to identify and classify objects within images.
This model can classify various fruits and vegetables. It has been trained on a dataset containing images of apples, oranges, bananas, tomatoes, carrots, and broccoli, among others.
The model uses deep learning techniques to identify the different types of fruits and vegetables with high accuracy.