Chongwei Shi Advances Biostatistical Methods and Computational Biology Through Deep Learning and Statistical Shape Analysis

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
IEEE

Android Malware Detection Using API Calls and Permissions with Random Forest Classifier

Abstract: Android malware poses a persistent and evolving threat to mobile security, considering its capability to compromise sensitive user data and evade traditional detection methods. While ...
EurekAlert!

AI-accelerated gas sensing: a first-principles–guided machine learning platform for black phosphorus sensors

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
GitHub

decision-tree-classifier

ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...
Hosted on MSN

Video: Forest officer fearlessly captures python with bare hands from Kerala pond

Mike Johnson reacts to Trump's "punishable by death" remark about Democrats US Navy trying to pull crashed aircraft from bottom of South China Sea The Ghislaine Maxwell Emails Zara Larsson fan becomes ...
Frontiers

Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
Frontiers

Machine learning enhanced acute heart failure phenotype prediction using natural language processing and random forest

Background: Heart failure (HF), with its distinct phenotypes, poses significant public health challenges. Early diagnosis of specific HF phenotypes is crucial for timely therapeutic intervention.
IEEE

Facilitating Seamless Communication through Voice-Enhanced Sign Language and Gesture Recognition with Random Forest Classifier and Graph Convolution Networks

Abstract: An innovative system designed to enhance communication for individuals using sign language. Developed in Python, the system leverages a Random Forest classifier to accurately interpret hand ...