We developed precompiled lexicons and classification rules as features for the following ML classifiers: logistic regression, random forest, and support vector machines (SVMs). These features were ...
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 ...
Audio signal processing has experienced rapid evolution in recent years, driven largely by developments in deep learning. Modern approaches now harness neural network architectures to extract ...
The extensive growth and use of electronic health records (EHRs) and extending medical literature have led to huge opportunities to automate the extraction of relevant clinical information that helps ...
In an era where sensitive data is a prime target for cyberattacks and compliance violations, effective data classification is the critical first step in safeguarding information. Recognizing the ...
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 ...
The objective of this data protection rule is to assist the UAB community in the protections requirements of data and systems based on the Data Classification Rule. 2.0 Scope and Applicability All UAB ...
Acoustic-Event Recognition: Source Classification A variety of signal-processing and ML techniques have been applied to solve the problem of audio classification, including matrix factorization, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback