IEEE

A Reinforcement Learning-Driven Algorithm for Rapid Path Replanning of Robot Navigation in Indoor Uncertain Discrete Environments

Abstract: In the context of indoor dense discrete environments, the rapid replanning of paths upon encountering novel obstacles has remained a formidable challenge. Traditional rule-based global path ...
IEEE

MPDA: A Massively Parallel Learning and Dependency-Aware Scheduling Algorithm for Data Processing Clusters

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...
IEEE

Hybrid Variational Quantum Algorithm Enhanced Subentire-Domain Basis Functions Method With High Learning Efficiency and Better Robustness

Abstract: The subentire-domain (SED) basis functions method is the most effective method for analyzing the electromagnetic (EM) properties of large-scale finite periodic structures (LFPSs). Recently, ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
IEEE

Prediction of Asthma Using Machine Learning Algorithms

Abstract: Asthma, a prevalent chronic respiratory condition, poses significant challenges to public health worldwide. Accurate and early prediction of asthma risk can greatly aid healthcare ...
IEEE

Classification of Music Genres based on Machine Learning SVM and CNN

Abstract: This study aims to compare the performance of two classification methods—Support Vector Machine (SVM) and Convolutional Neural Network (CNN)—in identifying music genres based on audio data ...
IEEE

Bi-Level Optimization of Electric Vehicle Charging Scheduling Using Hybrid Genetic Algorithm and Reinforcement Learning

Abstract: The efficient management of electric vehicle (EV) charging infrastructure is critical to meeting the growing demand for sustainable transportation. This study addresses the Electric Vehicle ...
IEEE

Decoding Machine Learning Algorithms for DR Detection

Abstract: Diabetic retinopathy is a serious eye disease which can lead to vision defects in diabetic patients. Early detection is important for preventing vision loss. Automating the detection process ...
IEEE

Application of CNN and KNN Algorithms for Casting Defect Classification

The study abstract outlines the utilization of advanced machine learning to identify and categorize casting defects such as Blowholes, Pinholes, and Swell with high precision, recall, and F1-scores.
IEEE

Indoor Positioning Deep Learning Network based on CNN-GAN for High-precision Bluetooth

Abstract: In recent years, Bluetooth Low Energy (BLE) positioning technology has garnered significant attention from researchers in the field of indoor localization. This study leverages IQ signal ...
IEEE

Design and Analysis of an Enhanced Cnn Accelerator for Deep Learning Applications

Abstract: This paper presents an optimized Convolutional Neural Network (CNN) accelerator with a focus on improving power efficiency and computational performance. Traditional CNN accelerators often ...
IEEE

A Hybrid Model using CNN and Genetic Algorithm for Pattern Classification of Interstitial Lung Disease

Abstract: Our objective is to develop an advanced computational approach to classify patterns of Interstitial Lung Disease(ILD) using a Hybrid model of Convolutional Neural Network(CNN) and Genetic ...