Muhammad Syafrudin

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Assistant Professor

Sejong University

South Korea

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About

Dr. Muhammad Syafrudin is an Assistant Professor at Sejong University in South Korea. His research areas encompass facial emotion recognition, diabetes prediction, fake news detection, cardiovascular disease prediction, and advancements in composting technologies. He has contributed to various scholarly articles, focusing on machine learning applications for health diagnostics and financial fraud detection, as well as natural language processing in relation to the circular economy.

Recent Grants

Grant: Close

Artificial Intelligence for Improving Diagnosis in Diabetes Care

Open Date: 2022-03-01

Close Date: 2023-04-01

Articles (30)

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Collaborators (5)

Jongtae Rhee

Dongguk University

SOUTH KOREA

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Norma Latif Fitriyani

Assistant Professor

Sejong University

SOUTH KOREA

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Yeong Hyeon Gu

Sejong University

SOUTH KOREA

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Dursun Aydin

University of Wisconsin-Madison

UNITED STATES

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Filip Benes

VSB - Technical University of Ostrava

CZECH REPUBLIC

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Muhammad Syafrudin

Research Interests

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About

Recent Grants

Articles (30)

A multi-scale simplicial transformer with graph attention for facial emotion recognition

Tab transformer with meta-ensemble learning approaches for enhanced diabetes prediction

Harnessing interpretable novel combination of GloVe embedding with deep CNN-BiLSTM neural network for fake news detection

A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases

Advancements in Composting Technologies for Efficient Soil Remediation of Polycyclic Aromatic Hydrocarbons (PAHs): A Mini Review

Enhanced Credit Card Fraud Detection Using Deep Hybrid CLST Model

Enhanced Interpretable Forecasting of Cryptocurrency Prices Using Autoencoder Features and a Hybrid CNN-LSTM Model

Tweeting Circular Economy: Unveiling Current Discourse Through Natural Language Processing

Improving thyroid disorder diagnosis via innovative stacking ensemble learning model

Human pose estimation in physiotherapy fitness exercise correction using novel transfer learning approach

Improving the performance of self-organizing map using reweighted zero-attracting method

Governing with Intelligence: The Impact of Artificial Intelligence on Policy Development

Enhancing Signature Verification Using Triplet Siamese Similarity Networks in Digital Documents

Color Modification of Silicone-Based Prosthetic Finger by 3D-Printed Mold

Exploring Tourist Experience through Online Reviews Using Aspect-Based Sentiment Analysis with Zero-Shot Learning for Hospitality Service Enhancement

AI in the Financial Sector: The Line between Innovation, Regulation and Ethical Responsibility

Block Cipher Nonlinear Component Generation via Hybrid Pseudo-Random Binary Sequence for Image Encryption

Novel Ensemble Learning Algorithm for Early Detection of Lower Back Pain Using Spinal Anomalies

Autonomous Vehicle Safety through the SIFT Method: A Conceptual Analysis

Efficient 5.8 GHz Microstrip Antennas for Intelligent Transportation Systems: Design, Fabrication, and Performance Analysis

ENGA: Elastic Net-Based Genetic Algorithm for human action recognition

Brain Pathology Classification of MR Images Using Machine Learning Techniques

Identifying Factors to Develop and Validate Social Vulnerability to Floods in Malaysia: A Systematic Review Study

Performance Analysis and Assessment of Type 2 Diabetes Screening Scores in Patients with Non-Alcoholic Fatty Liver Disease

Energy Usage Forecasting Model Based on Long Short-Term Memory (LSTM) and eXplainable Artificial Intelligence (XAI)

Utilizing Random Forest with iForest-Based Outlier Detection and SMOTE to Detect Movement and Direction of RFID Tags

Utilizing Random Forest with iForest-Based Outlier Detection and SMOTE to Detect Movement and Direction of RFID Tags

Optimisation of Knowledge Management (KM) with Machine Learning (ML) Enabled

Performance Analysis of Classification and Detection for PV Panel Motion Blur Images Based on Deblurring and Deep Learning Techniques

CRAS-YOLO: A Novel Multi-Category Vessel Detection and Classification Model Based on YOLOv5s Algorithm

Collaborators (5)

Jongtae Rhee

Norma Latif Fitriyani

Yeong Hyeon Gu

Dursun Aydin

Filip Benes

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