Structural defects that form during additive manufacturing, also known as 3D printing, are a barrier to some applications of this technology. Researchers used diagnostic tools and machine learning ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

By the end of the course, you will have developed the ability to understand how machine learning can be integrated into current business models and the challenges that this poses. Hear from some of ...

Projects that collect atomistic ML resources or foster communication within community. 🔗 ACE / GRACE support - Support forum for the Atomic Cluster Expansion (ACE) and extensions. 🔗 AI for Science ...

Understanding the electronic, structural, and dynamical properties of highly oriented pyrolytic graphite (HOPG) and its interface with water is crucial, as its layered structure, vacancy defects, and ...

Step 1: Place Your Model Make sure your trained model file (e.g., best.pt) is inside the models directory. Step 2: Build the Docker Image Open a terminal in the project root directory ...

This chapter discusses the basic steps involved in defect detection using image processing along with existing systems that use machine learning and artificial intelligence for the detection of ...

In the current deep learning research landscape, image processing technology faces significant challenges in lightweight defect detection despite its broad application in object detection. This study ...