Two-dimensional quaternion principal component analysis (2D-QPCA) is one of the successful dimensionality reduction methods for color face recognition. However, 2D-QPCA is sensitive to outliers. For ...

In the Moloto case, the Land Court had to consider factors like market value and the current use of the property on which a ...

The use of complex echo data is critical because it allows for separation of signal components based on motion, which is revealed through phase changes of the complex principal components. PCDE ...

Shoulder Innovations, Inc. plans a $100M IPO to fund R&D and growth in shoulder arthroplasty. Click for more about SI and its ...

Anxiety, the psychological and physiological state characterized by an anticipation of potential threats and a heightened ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Machine learning interview questions now focus on both theory and real-world applications.Understanding basics like overfitting, bias, and regres ...

Principal component analysis (PCA) was applied to the relative abundance ratios of 18 selected anthocyanins, followed by a Mahalanobis Distance Classification model for classifying unknown samples ...

Learn how variance analysis can help you control your budget, but also what are its limitations and drawbacks. Get some tips on how to use it effectively.

Syllabus: The NTA has put the official JEE Main 2026 Syllabus online on their website: jeemain.nta.nic.in. If you're planning ...