s heat history and part design is critical to manufacturing a high-quality part. On the other hand, understanding how to effectively design single and multi-cavity molds provides opportunities for material waste reduction for a more sustainable manufacturing technique. Simulating the process, material ...
Machine learning is a field of artificial intelligence that allows systems to learn and improve from experience without being explicitly programmed. It has become an increasingly popular topic in recent years due to the many practical applications it has in a variety of industries. In this blog, w...
Regression Testing is a Software Testing type in which test cases are re-executed in order to check whether the previous functionality of the application is working fine and the new changes have not introduced any new bugs. Regression Testing is a type of testing that is done to verify that ...
Nanoscale structure in rechargeable batteries determines the batteries’ performance. Inspecting the components of such batteries is useful when verifying material quality in the assembled cell and seeing the impacts of power cycling on material structure. Secondary cathode particles i...
So you want to start a new AI/ML initiative and now you’re quickly realizing that not only finding high-qualitytraining databut also data annotation will be a few of the challenging aspects of your project. The output of your AI & ML models is only as good as the data you use to ...
Driven by this key difference, the two methods focus on different use cases: unsupervised models are used for tasks like clustering, anomaly detection and dimensionality reduction that do not require a loss function, whereas self-supervised models are used for classification and regression tasks typica...
A probabilistic model is an unsupervised technique that helps us solve density estimation or “soft” clustering problems. In probabilistic clustering, data points are clustered based on the likelihood that they belong to a particular distribution. The Gaussian Mixture Model (GMM) is the one of the...
These trained models can be saved and reused. Enhanced precision in manual selection of objects is now available through new features in both the segmentation lasso tool and the brush tool. Explore the two use cases below to learn more:
The basic concept behind PINN training is that it can be thought of as an unsupervised strategy that does not require labelled data, such as results from prior simulations or experiments. The PINN algorithm is essentially a mesh-free technique that finds PDE solutions by converting the problem ...
Automatic facial expression recognition is a big challenge in human–computer interaction. Analyzing the changes in the face during a facial expression can be used for this purpose. In this paper, these changes are extracted as a number of motion vectors. These motion vectors are extracted using ...