COMPUTER VISION

CNN (Convolutional Neural Network)

Computer Vision

Definition

CNNs are neural networks specialized in image analysis, inspired by the biological visual system. They use convolutional filters to automatically detect features such as edges, textures, and complex shapes. They underpin nearly all industrial computer vision applications, from quality control to defect recognition in products.

Related terms

Computer Vision

Computer vision is the field of AI that enables computers to interpret images and video. It includes object recognition, quality inspection, license plate reading, and security video analysis. In Italian manufacturing, computer vision automates visual quality control, reducing defects reaching the customer and speeding up production lines.

AI Fundamentals

Deep Learning

Deep learning is an advanced machine learning technique that uses neural networks with many layers (hence 'deep') to learn complex data representations. It underpins modern speech recognition, machine translation, and text generation systems. It requires large amounts of data but produces extraordinarily accurate results.

Computer Vision

Image Classification

Image classification is the task of automatically assigning a category to an image. For example: 'conforming part' vs 'defective part', or automatically classifying scanned documents by type. CNNs (Convolutional Neural Networks) achieve accuracies above 99% on many industrial classification tasks.

EXPLORE

More terms in Computer Vision

Computer Vision

Object Detection

Object detection is the computer vision technique that identifies and locates specific objects in an image or video, drawing a bounding box around each one. It is used to count products on a conveyor belt, detect defects in components, and monitor safety areas. Algorithms like YOLO enable real-time detection, even on edge devices.

Image Classification

Segmentation

Image segmentation is the technique that classifies every single pixel of an image, precisely identifying the contours of each object. Unlike object detection which draws bounding boxes, segmentation delineates the exact shape. It is used for precise measurements, medical image analysis, and autonomous guidance of robots and vehicles in factories.

Face Recognition

Face recognition is the technology that identifies or verifies a person's identity by analyzing facial features. In businesses, it is used for access control, attendance tracking, and security. It is important to implement it in compliance with GDPR and European AI regulations, which place strict limits on the use of biometric recognition.

Quality Inspection

AI quality inspection uses computer vision to automatically verify product conformity on the production line. High-resolution cameras and deep learning algorithms detect scratches, dents, color defects, and dimensional irregularities with speed and consistency impossible for the human eye. It reduces returns and rework costs.

See all glossary terms →

Want to apply AI in your business?

Talk to us. The first call is free and no commitment.

Book a call