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Results for “"Sultan Alfarhood"”

16+ results

A multimodal approach to cross-lingual sentiment analysis with ensemble of transformer and LLM

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Md Saef Ullah Miah, Md. Mohsin Kabir, Talha Bin Sarwar, Mejdl Safran et al.

Journal: Scientific ReportsYear: 2024Citations: 163

Sentiment analysis is an essential task in natural language processing that involves identifying a text's polarity, whether it expresses positive, negative, or neutral sentiments. With the growth of social media and the Internet, sentiment analysis has become increasingly important in various fields...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time

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Md. Reazul Islam, Md. Mohsin Kabir, M. F. Mridha, Sultan Alfarhood et al.

Journal: SensorsYear: 2023Citations: 158

With an aging population and increased chronic diseases, remote health monitoring has become critical to improving patient care and reducing healthcare costs. The Internet of Things (IoT) has recently drawn much interest as a potential remote health monitoring remedy. IoT-based systems can gather an...

Health SciencesMedicineCardiology and Cardiovascular MedicineOpen Access
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A machine learning approach for vocal fold segmentation and disorder classification based on ensemble method

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S. M. Nuruzzaman Nobel, S M Masfequier Rahman Swapno, Md. Rajibul Islam, Mejdl Safran et al.

Journal: Scientific ReportsYear: 2024Citations: 50

In the healthcare domain, the essential task is to understand and classify diseases affecting the vocal folds (VFs). The accurate identification of VF disease is the key issue in this domain. Integrating VF segmentation and disease classification into a single system is challenging but important for...

Health SciencesMedicinePhysiologyOpen Access
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SPF-Net: Solar panel fault detection using U-Net based deep learning image classification

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Rifat Al Mamun Rudro, Kamruddin Nur, Md. Faruk Abdullah Al Sohan, M. F. Mridha et al.

Journal: Energy ReportsYear: 2024Citations: 43

The detection of faults in solar panels is essential for generating increased amounts of renewable green energy. Solar panels degrade over time due to physical damage, dust, or other faults. Numerous studies have been conducted to detect and monitor solar panel faults in real-time. This research exa...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Privacy-Preserving On-Screen Activity Tracking and Classification in E-Learning Using Federated Learning

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Durjoy Mistry, M. F. Mridha, Mejdl Safran, Sultan Alfarhood et al.

Journal: IEEE AccessYear: 2023Citations: 42

E-learning, a modern method of education that utilizes electronic technologies such as computers, mobile devices, and the internet, has experienced a significant surge in adoption and usage in recent years. While it has the potential to reach every corner of the world, it also creates an opportunity...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Addressing Uncertainty in Imbalanced Histopathology Image Classification of HER2 Breast Cancer: An Interpretable Ensemble Approach With Threshold Filtered Single Instance Evaluation (SIE)

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Md Sakib Hossain Shovon, M. F. Mridha, Khan Md. Hasib, Sultan Alfarhood et al.

Journal: IEEE AccessYear: 2023Citations: 37

Breast Cancer (BC) is among women’s most lethal health concerns. Early diagnosis can alleviate the mortality rate by helping patients make efficient treatment decisions. Human Epidermal Growth Factor Receptor (HER2) has become one the most lethal subtype of BC. According to the College of American P...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Multi task opinion enhanced hybrid BERT model for mental health analysis

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Md. Mithun Hossain, M. Jahangir Hossain, M. F. Mridha, Mejdl Safran et al.

Journal: Scientific ReportsYear: 2025Citations: 36

Understanding the nuanced emotions and points of view included in user-generated content remains challenging, even though text data analysis for mental health is a crucial instrument for assessing emotional well-being. Most current models neglect the significance of integrating viewpoints in compreh...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Palm Leaf Health Management: A Hybrid Approach for Automated Disease Detection and Therapy Enhancement

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S. M. Nuruzzaman Nobel, Md Asif Imran, Nahida Zaman Bina, Md. Mohsin Kabir et al.

Journal: IEEE AccessYear: 2024Citations: 36

Deep Learning and computer vision have become potent agricultural technologies in recent years. These technologies are essential for identifying hazardous plant leaf diseases, which significantly impact crop quality and productivity. The precise distinction between healthy and damaged palm leaves is...

Life SciencesAgricultural and Biological SciencesPlant ScienceOpen Access
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GLD-Det: Guava Leaf Disease Detection in Real-Time Using Lightweight Deep Learning Approach Based on MobileNet

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Md. Mustak Un Nobi, Md. Rifat, M. F. Mridha, Sultan Alfarhood et al.

Journal: AgronomyYear: 2023Citations: 33

The guava plant is widely cultivated in various regions of the Sub-Continent and Asian countries, including Bangladesh, due to its adaptability to different soil conditions and climate environments. The fruit plays a crucial role in providing food security and nutrition for the human body. However, ...

Life SciencesAgricultural and Biological SciencesPlant ScienceOpen Access
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Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel

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Istiak Mahmud, Md. Mohsin Kabir, M. F. Mridha, Sultan Alfarhood et al.

Journal: DiagnosticsYear: 2023Citations: 33

Accurate prediction of heart failure can help prevent life-threatening situations. Several factors contribute to the risk of heart failure, including underlying heart diseases such as coronary artery disease or heart attack, diabetes, hypertension, obesity, certain medications, and lifestyle habits ...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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Cauli-Det: enhancing cauliflower disease detection with modified YOLOv8

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Md. Sazid Uddin, Md. Khairul Alam Mazumder, Afrina Jannat Prity, M. F. Mridha et al.

Journal: Frontiers in Plant ScienceYear: 2024Citations: 32

Cauliflower cultivation plays a pivotal role in the Indian Subcontinent's winter cropping landscape, contributing significantly to both agricultural output, economy and public health. However, the susceptibility of cauliflower crops to various diseases poses a threat to productivity and quality. Thi...

Life SciencesAgricultural and Biological SciencesPlant ScienceOpen Access
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Ensemble of hybrid model based technique for early detecting of depression based on SVM and neural networks

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Dip Kumar Saha, Tuhin Hossain, Mejdl Safran, Sultan Alfarhood et al.

Journal: Scientific ReportsYear: 2024Citations: 26

The prevalence of depression has increased dramatically over the last several decades: it is frequently overlooked and can have a significant impact on both physical and mental health. Therefore, it is crucial to develop an automated detection system that can instantly identify whether a person is d...

Health SciencesMedicineComplementary and alternative medicineOpen Access
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Fusing global context with multiscale context for enhanced breast cancer classification

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Niful Islam, Khan Md. Hasib, M. F. Mridha, Sultan Alfarhood et al.

Journal: Scientific ReportsYear: 2024Citations: 23

Breast cancer is the second most common type of cancer among women. Prompt detection of breast cancer can impede its advancement to more advanced phases, thereby elevating the probability of favorable treatment consequences. Histopathological images are commonly used for breast cancer classification...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders

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Mohammad Sayem Chowdhury, Tofayet Sultan, Nusrat Jahan, M. F. Mridha et al.

Journal: Skin Research and TechnologyYear: 2024Citations: 21

BACKGROUND: Hair and scalp disorders present a significant challenge in dermatology due to their clinical diversity and overlapping symptoms, often leading to misdiagnoses. Traditional diagnostic methods rely heavily on clinical expertise and are limited by subjectivity and accessibility, necessitat...

Health SciencesMedicineUrologyOpen Access
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Segmentation for mammography classification utilizing deep convolutional neural network

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Dip Kumar Saha, Tuhin Hossain, Mejdl Safran, Sultan Alfarhood et al.

Journal: BMC Medical ImagingYear: 2024Citations: 19

BACKGROUND: Mammography for the diagnosis of early breast cancer (BC) relies heavily on the identification of breast masses. However, in the early stages, it might be challenging to ascertain whether a breast mass is benign or malignant. Consequently, many deep learning (DL)-based computer-aided dia...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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