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Results for “"Anupam Kumar Bairagi"”

16+ results

A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework

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Mehedi Masud, Niloy Sikder, Abdullah-Al Nahid, Anupam Kumar Bairagi et al.

Journal: SensorsYear: 2021Citations: 445

The field of Medicine and Healthcare has attained revolutionary advancements in the last forty years. Within this period, the actual reasons behind numerous diseases were unveiled, novel diagnostic methods were designed, and new medicines were developed. Even after all these achievements, diseases l...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review

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Suliman Abdulmalek, Abdul Nasir, Waheb A. Jabbar, Mukarram A. M. Almuhaya et al.

Journal: HealthcareYear: 2022Citations: 394

The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitor...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach

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Madyan Alsenwi, Nguyen H. Tran, Mehdi Bennis, Shashi Raj Pandey et al.

Journal: University of Oulu Repository (University of Oulu)Year: 2021Citations: 321

In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile BroadBand (eMBB). While eMBB services focus on high data rates, URLLC is very strict in terms of latency a...

Physical SciencesEngineeringElectrical and Electronic Engineering
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Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning

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Nusrat Jahan Prottasha, Abdullah As Sami, Md. Kowsher, Saydul Akbar Murad et al.

Journal: SensorsYear: 2022Citations: 231

The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals' emotions empowers sentiment analysis. However, sentiment analysis becomes even more challenging due to a scarcity of standardized l...

Health SciencesMedicineCardiology and Cardiovascular MedicineOpen Access
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Severity Classification of Diabetic Retinopathy Using an Ensemble Learning Algorithm through Analyzing Retinal Images

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Niloy Sikder, Mehedi Masud, Anupam Kumar Bairagi, Abu Shamim Mohammad Arif et al.

Journal: SymmetryYear: 2021Citations: 143

Diabetic Retinopathy (DR) refers to the damages endured by the retina as an effect of diabetes. DR has become a severe health concern worldwide, as the number of diabetes patients is soaring uncountably. Periodic eye examination allows doctors to detect DR in patients at an early stage to initiate p...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data

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Md. Abdul Awal, Mehedi Masud, Md. Shahadat Hossain, Abdullah Al-Mamun Bulbul et al.

Journal: IEEE AccessYear: 2021Citations: 86

The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people. To get rid of this unexpected situation, quick identification of COVID-19 patien...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction

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Md. Mehedi Hassan, Md. Mahedi Hassan, Farhana Yasmin, Md. Asif Rakib Khan et al.

Journal: Decision Analytics JournalYear: 2023Citations: 79

Breast cancer is the most common life-threatening cancer in women and one of the leading causes of death. Early diagnosis is one of the best defenses against the spread of breast cancer. Machine learning (ML) tools are now available for cancer detection and prediction. This study presents a comparat...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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4D: A Real-Time Driver Drowsiness Detector Using Deep Learning

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Israt Jahan, K. M. Aslam Uddin, Saydul Akbar Murad, Md Saef Ullah Miah et al.

Journal: ElectronicsYear: 2023Citations: 76

There are a variety of potential uses for the classification of eye conditions, including tiredness detection, psychological condition evaluation, etc. Because of its significance, many studies utilizing typical neural network algorithms have already been published in the literature, with good resul...

Social SciencesPsychologyExperimental and Cognitive PsychologyOpen Access
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NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data

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Rezuana Haque, Md. Mehedi Hassan, Anupam Kumar Bairagi, Sheikh Mohammed Shariful Islam

Journal: Scientific ReportsYear: 2024Citations: 72

Brain tumors (BTs) are one of the deadliest diseases that can significantly shorten a person's life. In recent years, deep learning has become increasingly popular for detecting and classifying BTs. In this paper, we propose a deep neural network architecture called NeuroNet19. It utilizes VGG19 as ...

Life SciencesNeuroscienceNeurologyOpen Access
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Attention to Monkeypox: An Interpretable Monkeypox Detection Technique Using Attention Mechanism

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Avi Deb Raha, Mrityunjoy Gain, Rameswar Debnath, Apurba Adhikary et al.

Journal: IEEE AccessYear: 2024Citations: 70

In the wake of COVID-19, rising monkeypox cases pose a potential pandemic threat. While less severe than COVID-19, its increasing spread underscores the urgency of early detection and isolation to control the disease. The main difficulty in diagnosing monkeypox arises from its prolonged diagnostic p...

Life SciencesImmunology and MicrobiologyVirologyOpen Access
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Machine Learning-Based Rainfall Prediction: Unveiling Insights and Forecasting for Improved Preparedness

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Md. Mehedi Hassan, Mohammad Abu Tareq Rony, Md. Asif Rakib Khan, Md. Mahedi Hassan et al.

Journal: IEEE AccessYear: 2023Citations: 58

Rainfall prediction plays a crucial role in raising awareness about the potential dangers associated with rain and enabling individuals to take proactive measures for their safety. This study aims to utilize machine learning algorithms to accurately predict rainfall, considering the significant impa...

Physical SciencesEnvironmental ScienceEnvironmental EngineeringOpen Access
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MTD-DHJS: Makespan-Optimized Task Scheduling Algorithm for Cloud Computing With Dynamic Computational Time Prediction

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Pallab Banerjee, Sharmistha Roy, Anurag Sinha, Md. Mehedi Hassan et al.

Journal: IEEE AccessYear: 2023Citations: 54

Cloud computing has revolutionized the management and analysis of data for organizations, offering scalability, flexibility, and cost-effectiveness. Effective task scheduling in cloud systems is crucial to optimize resource utilization and ensure timely job completion. This research presents a novel...

Physical SciencesComputer ScienceInformation SystemsOpen Access
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A Pneumonia Diagnosis Scheme Based on Hybrid Features Extracted from Chest Radiographs Using an Ensemble Learning Algorithm

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Mehedi Masud, Anupam Kumar Bairagi, Abdullah-Al Nahid, Niloy Sikder et al.

Journal: Journal of Healthcare EngineeringYear: 2021Citations: 53

Pneumonia is a fatal disease responsible for almost one in five child deaths worldwide. Many developing countries have high mortality rates due to pneumonia because of the unavailability of proper and timely diagnostic measures. Using machine learning-based diagnosis methods can help to detect the d...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Recognition of Sunflower Diseases Using Hybrid Deep Learning and Its Explainability with AI

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Promila Ghosh, Amit Kumar Mondal, Sajib Chatterjee, Mehedi Masud et al.

Journal: MathematicsYear: 2023Citations: 52

Sunflower is a crop that has many economic values and ornamental usages. However, its production can be hampered due to various diseases such as downy mildew, gray mold, and leaf scars, and it is challenging for farmers to identify disease-prone conditions with traditional approaches. Thus, a comput...

Life SciencesAgricultural and Biological SciencesPlant ScienceOpen Access
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SG-PBFS: Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment

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Saydul Akbar Murad, Zafril Rizal M Azmi, Abu Jafar Md Muzahid, Md. Khairul Bashar Bhuiyan et al.

Journal: Future Generation Computer SystemsYear: 2023Citations: 48
Physical SciencesComputer ScienceInformation Systems
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