AI (Artificial Intelligence) is a field of science focused on understanding and solving cognitive problems typically associated with human intelligence, such as image recognition, learning, and creativity. Essentially, artificial intelligence is a branch of computer science viewed from this perspective.
Humanity continues to draw value from this field across every sector. While applications vary by industry, these processes are generally supported by monitoring equipment like cameras and sensors, system codes, and human-generated content, all of which contribute vast amounts of data for AI.
The goal of AI—short for artificial intelligence—is to derive meaning from all the data it collects, leading to systems that can learn independently. These advancements allow humanity to move forward, with the level of progress rising as AI technology evolves daily.
One of the major sectors leveraging AI is the textile industry. Image processing systems and AI programs play a significant role, particularly in fabric quality assessment within the textile sector.
What Are Fabric Inspection Methods?
In textiles, fabric quality can be assessed using various methods, including the following:
Visual Inspection (Manual Control)
AI and Machine Learning-Supported Systems
Optical and Image Processing-Based Control
Spectrophotometric Analysis
International and Mechanical Testing
Chemical Testing
Thermal and Moisture Resistance Testing
What Are the Advantages of Artificial Intelligence and Machine Learning-Supported Systems?
Among the options, AI and Machine Learning-Supported Systems offer a time-saving, automated alternative to manual control. For businesses aiming to keep up with today’s technology, implementing this option is essential.
AI and machine learning-supported systems bring advantages such as high speed and efficiency, scalability, cost savings, comprehensive data analysis, adaptability, and reduced human error.
Alongside these benefits, their complex nature requires initial training, regular maintenance, and updates. A strong technological foundation is essential to ensure that AI investments meet expectations and add value to the business.