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Scientists who modeled the lost canals of China's Liangzhu city confirmed a 5,000-year-old hydraulic system that rewrites early Chinese engineering

Water leaves a memory in the land. Even after thousands of years, it lingers as faint ridges and subtle curves that only ...
Bloomberg L.P.

Meta to Pay $140 Million to Use Black Forest Labs AI for Images

Meta Platforms Inc. has signed a multi-year contract worth more than $100 million to use technology from AI image startup Black Forest Labs, the latest investment by the social media firm to expand ...
Frontiers

Machine learning differentiation of rheumatoid arthritis-Sjögren’s syndrome overlap from Sjögren’s syndrome with polyarthritis

Department of Rheumatology and Immunology, Ningbo NO.2 Hospital, Ningbo, Zhejiang, China Objective: This study aimed to evaluate the utility of machine learning algorithms in differentiating ...
IEEE

Machine Learning Driven Islanding Detection using Random Forest and Scalogram

Abstract: Islanding is a problem caused by distributed generation sources, causing potential damage to clients and equipment. To meet IEEE 1547 DG interconnection requirements, it must be detected ...
Frontiers

A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021)

Background: Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical settings where fundus cameras are not accessible.
Scientific Research Publishing

Breiman, L. (2001). Random Forests. Machine Learning, 45, 5-32.

ABSTRACT: Accurate canopy height estimation is critical for forest management and carbon monitoring in Zambia’s ecologically diverse landscapes. This study developed a high-resolution canopy height ...
IEEE

Enhancing Accuracy in Image Recognition for Deepfaked Images using Convolutional Networks Compared with Random Forest Algorithm

Abstract: The primary goal of this study is to improve the accuracy of deepfake image recognition using convolutional neural networks (CNN) and compare the results to Random Forest approaches.
Houston Public Media

UH Moment: Researchers Use Machine Learning to Map Brain Changes from Heroin Addiction

Researchers at the University of Houston and the University of Cincinnati are using machine learning to create a clearer picture of how heroin affects the brain, potentially opening new doors for ...
Scientific Research Publishing

Adugna, T., Xu, W., & Fan, J. (2022). Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images ...

ABSTRACT: Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral ...