AI helps find trees in a forest: Researchers achieve 3D forest reconstruction from remote sensing data

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...
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 ...
IEEE

Identification of Cyber Bullying Using XGBoost Compared to Random Forest Classifier to Improve Accuracy

Abstract: The study aims to improve the accuracy of cyberbullying detection. Compared to the Random Forest classifier, utilize XGBoost to improve accuracy. In this study, two groups were compared. The ...
Scientific Research Publishing

Pazhanikumar, K. and KuzhalVoiMozhi, S.N. (2023) Remote Sensing Image Classification Using Modified Random Forest with Empirical Loss Function through Crowd-Sourced Data ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
GitHub

Implement Random Forest Algorithm for Encrypted Traffic Classification

@IvanNardi As per our initial discussion: Is your feature request related to a problem? Please describe. Detecting malware and covert communications within encrypted traffic, especially when ...