Fentanyl or phony? Machine learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
AZ Animals

Tiny AI Devices Are Listening for Poachers in the World’s Most Remote Forests

TinyML sensors detect chainsaws, gunshots, and animal calls offline, offering a new way to protect wildlife in remote ...
IEEE

Detecting HLS Hardware Trojans using Random Forest Classifier

Abstract: High-level Synthesis (HLS) generated IP designs are widely and effectively used in several image/video processing applications, consumer electronics applications as well as multimedia ...
GitHub

o-ronin-o/decision-trees-random-forest_from_scratch_probabilistic-classifier

Here's the complete project structure: decision-trees-random-forest_from_scratch_probabilistic-classifier/ │ ├── data/ │ ├── raw ...
Scientific Research Publishing

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

ABSTRACT: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of ...
Scientific Research Publishing

Liaw, A. and Wiener, M. (2002) Classification and Regression by Random Forest. R News, 2, 18-22.

ABSTRACT: Predicting knowledge of tuberculosis (TB) could imply several significant changes in the management, control and prevention of this disease. These would be based on advanced technological ...
Frontiers

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
IEEE

A Hybrid PSO-Random Forest Framework for Real-Time Vehicle Classification Using Roadside LiDAR

Abstract: Intelligent transportation systems are increasingly reliant on precise and efficient vehicle classification to support traffic management, safety applications, and infrastructure planning.
GitHub

Credit-Card-Fraud-Detection-with-Random-Forest-Classifier

The goal of this project is indentify fraudulent transactions while minimizing false positives (non-fraudulent transactions flagged as fraud) and false negatives (missed fraudulent transations). The ...