Muhammad Naufal Rachmatullah

About Muhammad Naufal Rachmatullah

Muhammad Naufal Rachmatullah, With an exceptional h-index of 16 and a recent h-index of 16 (since 2020), a distinguished researcher at Universitas Sriwijaya, specializes in the field of Machine Learning, Deep Learning, Digital Image Processing, Computer Vision.

His recent articles reflect a diverse array of research interests and contributions to the field:

Health-related Data Analysis using Metaheuristic Optimization and Machine Learning

Keyphrase Extraction Using TextRank for Indonesian Text

Development of a machine learning model for predicting abnormalities of commercial airplanes

Video Annomaly Classification Using Convolutional Neural Network

XU-NetI: Simple U-Shaped Encoder-Decoder Network for Accurate Imputation of Multivariate Missing Data

Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm

Video Based Fish Species Detection Using Faster Region Convolution Neural Network

Segmentation of Skin Lesions Using Convolutional Neural Networks

Muhammad Naufal Rachmatullah Information

University

Position

Intelligent System Research Group Faculty of Computer Science

Citations(all)

772

Citations(since 2020)

770

Cited By

144

hIndex(all)

16

hIndex(since 2020)

16

i10Index(all)

21

i10Index(since 2020)

21

Email

University Profile Page

Google Scholar

Muhammad Naufal Rachmatullah Skills & Research Interests

Machine Learning

Deep Learning

Digital Image Processing

Computer Vision

Top articles of Muhammad Naufal Rachmatullah

Health-related Data Analysis using Metaheuristic Optimization and Machine Learning

IEEE Access

2024/4/16

Keyphrase Extraction Using TextRank for Indonesian Text

Sriwijaya Journal of Informatics and Applications

2024/3/10

Fadel Muhammad
Fadel Muhammad

H-Index: 0

Novi Yusliani
Novi Yusliani

H-Index: 4

Muhammad Naufal Rachmatullah
Muhammad Naufal Rachmatullah

H-Index: 7

Development of a machine learning model for predicting abnormalities of commercial airplanes

Scientific Reports

2021/1/13

Video Annomaly Classification Using Convolutional Neural Network

Computer Engineering and Applications Journal

2024/2/1

Muhammad Naufal Rachmatullah
Muhammad Naufal Rachmatullah

H-Index: 7

Sutarno Sutarno
Sutarno Sutarno

H-Index: 5

Rahmat Fadli Isnanto
Rahmat Fadli Isnanto

H-Index: 1

XU-NetI: Simple U-Shaped Encoder-Decoder Network for Accurate Imputation of Multivariate Missing Data

2023/8/7

Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm

BMC Medical Informatics and Decision Making

2023/7/28

Video Based Fish Species Detection Using Faster Region Convolution Neural Network

Computer Engineering and Applications Journal

2023/6/1

Muhammad Naufal Rachmatullah
Muhammad Naufal Rachmatullah

H-Index: 7

Segmentation of Skin Lesions Using Convolutional Neural Networks

Computer Engineering and Applications Journal

2023/2/1

Real time mobile AI-assisted cervicography interpretation system

Informatics in Medicine Unlocked

2023/1/1

Data analysis of commercial aircraft landing on the runway airports in Indonesia

Zeszyty Naukowe. Transport/Politechnika Śląska

2023

Deep learning-based real time detection for cardiac objects with fetal ultrasound video

Informatics in Medicine Unlocked

2023/1/1

Empowering AI-Diagnosis: Deep Learning Abilities for Accurate Atrial Fibrillation Classification.

International Journal of Online & Biomedical Engineering

2023/12/6

Forecasting Of Intensive Care Unit Patient Heart Rate Using Long Short-Term Memory

Computer Engineering and Applications Journal

2023/10/1

Classification of Atrial Fibrillation In ECG Signal Using Deep Learning

Computer Engineering and Applications Journal

2023/10/1

Muhammad Fachrurrozi
Muhammad Fachrurrozi

H-Index: 7

Muhammad Naufal Rachmatullah
Muhammad Naufal Rachmatullah

H-Index: 7

Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model

BMC bioinformatics

2023/9/27

Accurate Fetal QRS-Complex Classification from Abdominal Electrocardiogram Using Deep Learning

International Journal of Computational Intelligence Systems

2023/9/26

CervicoXNet: an automated cervicogram interpretation network

Medical & Biological Engineering & Computing

2023/9

Robust electrocardiogram delineation model for automatic morphological abnormality interpretation

Scientific Reports

2023/8/23

Deep Learning for Fetal QRS-complex Classification in Noninvasive Fetal Electrocardiogram

2023/8/9

A Deep Learning Approach for Automated Prediction of Cardiac Arrest from Vital Sign Data of Intensive Care Unit Patients

2023/8/9

See List of Professors in Muhammad Naufal Rachmatullah University(Universitas Sriwijaya)