Loading [MathJax]/extensions/MathZoom.js
Nur Intan Raihana Ruhaiyem - IEEE Xplore Author Profile
Subscribe
ADVANCED SEARCH

Author details

< Back

Nur Intan Raihana Ruhaiyem

Publications
8
Citations
32
Publications by Year
20172025
Co-Authors:
Show All Co-Authors (12)
Image of author Nur Intan Raihana Ruhaiyem

Nur Intan Raihana Ruhaiyem

Affiliation

School of Computer Science
Universiti Sains Malaysia
Gelugor, Malaysia

Publication Topics

Biography

Nur Intan Raihana Ruhaiyem received the Ph.D. degree specializing in computational cell biology from The University of Queensland, Australia, in 2014. She is currently a Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia. Her research interests include in the areas of medical image processing and analysis, computer vision, and data visualization and analysis. She is also a Certified Trainer with Human Resources Development Corporation (HRD Corporation), Malaysia, and has been handling many workshops in the field of data science specifically in data visualization and analytics, since 2018.(Based on document published on 14 October 2022).
Publications
8
Citations
32
Publications by Year
20172025
Co-Authors:
Show All Co-Authors (12)
Author's Published Works

Showing 1-8 of 8 results

  • Sort

Filter Results

Show

Sort By

Results

A 3M-Hybrid Model for the Restoration of Unique Giant Murals: A Case Study on the Murals of Yongle Palace

Jing Yang;Nur Intan Raihana Ruhaiyem;Chichun Zhou

IEEE Access
Year: 2025 | Volume: 13 | Journal Article |
The unique giant murals of Yongle Palace, as valuable cultural heritage, have suffered damage and urgently require restoration. Deep learning inpainting algorithm offers promising solutions for image restoration. However, the restoration of unique giant murals presents two challenges: 1) The unique and scarce data of mural poses significant training difficulties, and 2) the giant size leads to a w...Show More

A 3M-Hybrid Model for the Restoration of Unique Giant Murals: A Case Study on the Murals of Yongle Palace

Jing Yang;Nur Intan Raihana Ruhaiyem;Chichun Zhou

Year: 2025 | Volume: 13 | Journal Article |

Review of Deep Learning-Based Image Inpainting Techniques

Jing Yang;Nur Intan Raihana Ruhaiyem

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
Cited by: Papers (2)
The deep learning-based image inpainting models discussed in this review are critical image processing techniques for filling in missing or removed regions in static planar images, and they have been extensively researched and applied. However, due to the rapid advancements in deep learning technologies, existing review studies exhibit shortcomings: in 1) providing a comprehensive and systematic c...Show More

Review of Deep Learning-Based Image Inpainting Techniques

Jing Yang;Nur Intan Raihana Ruhaiyem

Year: 2024 | Volume: 12 | Journal Article |

BoZFEx – A New Feature Extraction Based on Bounded-Zone Method for Handwriting Character Recognition

Nik Nur Adlin Nik Qausbee;Nur Intan Raihana Ruhaiyem

2023 IEEE International Conference on Computing (ICOCO)
Year: 2023 | Conference Paper |
The selection of a suitable set of features to represent input samples is one of the most influential elements in a successful optical character recognition, OCR pipeline. The feature extraction phase plays a vital role in extracting the appropriate features that yield minimum classification error, especially in cursive or fibrous handwriting. This study proposed a new feature extraction; BoZFEx -...Show More

BoZFEx – A New Feature Extraction Based on Bounded-Zone Method for Handwriting Character Recognition

Nik Nur Adlin Nik Qausbee;Nur Intan Raihana Ruhaiyem

Year: 2023 | Conference Paper |

TL-AttSharpNet: Automated Lung Image Segmentation using Transfer Learning with Depthwise Convolution and Attention

Mohammad Raihan Goni;Ayokunle Olalekan Ige;Nur Intan Raihana Ruhaiyem

2023 IEEE 2nd National Biomedical Engineering Conference (NBEC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The global community has recently been impacted by the COVID-19 pandemic, regarded as the biggest public health emergency the world has ever seen. Covid-19 has been shown to provoke pneumonia, among other diseases characterized by lung inflammation. Imaging exams such as chest X-rays (CXR) are often used because they are cheap, fast, widespread, and use less radiation. Even though typical CXR imag...Show More

TL-AttSharpNet: Automated Lung Image Segmentation using Transfer Learning with Depthwise Convolution and Attention

Mohammad Raihan Goni;Ayokunle Olalekan Ige;Nur Intan Raihana Ruhaiyem

Year: 2023 | Conference Paper |

Salient feature extraction using Attention for Brain Tumor segmentation

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem

2022 IEEE International Conference on Computing (ICOCO)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
The brain tumor is recognized as one of the most frequent tumors, with a significant mortality rate associated with its development. Segmentation of brain tumors involves distinguishing normal brain tissue from malignant tissue. When evaluating brain tumors, it is possible to determine the existence of tumor tissue quickly. However, accurate and reproducible segmentation and characterization of an...Show More

Salient feature extraction using Attention for Brain Tumor segmentation

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem

Year: 2022 | Conference Paper |

Brain Vessel Segmentation Using Deep Learning—A Review

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem;Muzaimi Mustapha;Anusha Achuthan;Che Mohd Nasril Che Mohd Nassir

IEEE Access
Year: 2022 | Volume: 10 | Journal Article |
Cited by: Papers (16)
This article provides a comprehensive review of deep learning-based blood vessel segmentation of the brain. Cerebrovascular disease develops when blood arteries in the brain are compromised, resulting in severe brain injuries such as ischemic stroke, brain hemorrhages, and many more. Early detection enables patients to obtain more effective treatment before becoming critically unwell. Due to the s...Show More

Brain Vessel Segmentation Using Deep Learning—A Review

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem;Muzaimi Mustapha;Anusha Achuthan;Che Mohd Nasril Che Mohd Nassir

Year: 2022 | Volume: 10 | Journal Article |

CubeLink System – An on Board Data Handling(OBDH) for Space Exploration on Miniaturized Satellite

Nurul Hazirah Mohd-Isah;Nur Intan Raihana Ruhaiyem;Normah Abdul-Latip

2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)
Year: 2020 | Conference Paper |
Cited by: Papers (5)
In year 1969 when Radio Amateur Satellite Corporation (AMSAT) was formed; building satellites are costly. Hence, a miniaturized satellite such as CanSat and CubeSat, is introduced. The invention of microelectronics has produced these satellites with most of the functionality of an OSCAR satellite, allowing a more cost-effective space research to be conducted. Generally, both CubeSat with a 10 cm c...Show More

CubeLink System – An on Board Data Handling(OBDH) for Space Exploration on Miniaturized Satellite

Nurul Hazirah Mohd-Isah;Nur Intan Raihana Ruhaiyem;Normah Abdul-Latip

Year: 2020 | Conference Paper |

An overview of hand-based multimodal biometrie system using multi-classifier score fusion with score normalization

Karthikeyan Shanmugasundaram;Ahmad Sufril Azlan Mohamed;Nur Intan Raihana Ruhaiyem

2017 International Conference on Signal Processing and Communication (ICSPC)
Year: 2017 | Conference Paper |
Cited by: Papers (5)
In the emerging trends of biometrie authentication, multimodal biometries getting more attention from researchers due to its universality, uniqueness, no intra-class variations, no inter-class similarities, and anti-spoofing attacks than unimodal biometrics. Hand-based multibiometric system is the most successful and used in many real time systems especially law enforcement and forensics. Moreover...Show More

An overview of hand-based multimodal biometrie system using multi-classifier score fusion with score normalization

Karthikeyan Shanmugasundaram;Ahmad Sufril Azlan Mohamed;Nur Intan Raihana Ruhaiyem

Year: 2017 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.