LEARNING
Convolutional neural networks (CNN) are used to automatically learn relevant visual features from images, recognizing patterns, shapes, textures, or other features that distinguish different categories.
During the training phase, the algorithm is fed with a large set of correctly labeled training data containing images belonging to their respective categories.
Applications
QUALITY CONTROL
The algorithm can be used for automatic quality control, such as classifying metal pieces based on their dimensions, shape, or the presence of defects.
FOOD PRODUCTION MONITORING
The algorithm can verify product compliance with production specifications, classifying food products based on factors such as size, shape, consistency, or the presence of unwanted contaminants.
PRODUCT CLASSIFICATION
In manufacturing and shipping environments, the algorithm can automatically classify products based on their sizes, enabling efficient organization of products.