Abstract: The utilization of multimodal data from multisensors (e.g., hyperspectral and light detection ranging (LiDAR) data) to classify ground objects has been an important topic in remote sensing ...

Artificial intelligence brings to classification a scalable, accurate alternative. Using natural language processing and ...

Biologists are quietly rewriting what it means to be alive, and the human body has become one of their strangest frontiers.

Here are some memorable examples of when that process paid off this year: when a few numbers, the shape of a line, or the ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

The move to reclassify cannabis from a Schedule I to a Schedule III drug could spark new studies into pain, aging and women's health, Dr. Staci Gruber tells GBH's All Things Considered.

Background: The performance of a classification algorithm eventually reaches a point of diminishing returns, where the additional sample added does not improve the results. Thus, there is a need to ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the right time. Then, she details the proper unstructured data preparation for AI.

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

USU’s data classification system organizes data into three tiers based on the potential adverse impact of unauthorized access, use, or alteration. This system helps us manage risks associated with ...

In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...