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Field: Artificial intelligence

Flood susceptibility modelling using advanced ensemble machine learning models

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Abu Reza Md. Towfiqul Islam, Swapan Talukdar, Susanta Mahato, Sonali Kundu et al.

Journal: Geoscience Frontiers
Year: 2020
Citations: 558

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of fl...

Physical SciencesEnvironmental ScienceGlobal and Planetary ChangeOpen Access
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International Journal of Advanced Research in Computer and Communication Engineering

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Nirjhor Anjum, Md Rubel Chowdhury

Journal: SSRN Electronic JournalYear: 2024Citations: 557
Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Machine-Learning-Based Disease Diagnosis: A Comprehensive Review

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Md Manjurul Ahsan, Shahana Akter Luna, Zahed Siddique

Journal: HealthcareYear: 2022Citations: 550

Globally, there is a substantial unmet need to diagnose various diseases effectively. The complexity of the different disease mechanisms and underlying symptoms of the patient population presents massive challenges in developing the early diagnosis tool and effective treatment. Machine learning (ML)...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images

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Sivaramakrishnan Rajaraman, Sameer Antani, Mahdieh Poostchi, Kamolrat Silamut et al.

Journal: PeerJYear: 2018Citations: 549

parasites transmitted through the bite of female Anopheles mosquito. Microscopists commonly examine thick and thin blood smears to diagnose disease and compute parasitemia. However, their accuracy depends on smear quality and expertise in classifying and counting parasitized and uninfected cells. Su...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Exploring the effects of trust, task interdependence and virtualness on knowledge sharing in teams

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D. Sandy Staples, Jane Webster

Journal: Information Systems JournalYear: 2008Citations: 545

Abstract The sharing of knowledge within teams is critical to team functioning. However, working with team members who are in different locations (i.e. in virtual teams) may introduce communication challenges and reduce opportunities for rich interactions, potentially affecting knowledge sharing and...

Social SciencesCommunicationKnowledge Management and Sharing
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Maternal health in poor countries: the broader context and a call for action

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Véronique Filippi, Carine Ronsmans, Oona M. R. Campbell, Wendy Graham et al.

Journal: The LancetYear: 2006Citations: 543

In this paper, we take a broad perspective on maternal health and place it in its wider context. We draw attention to the economic and social vulnerability of pregnant women, and stress the importance of concomitant broader strategies, including poverty reduction and women's empowerment. We also con...

Health SciencesMedicinePediatrics, Perinatology and Child Health
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Identification and recognition of rice diseases and pests using convolutional neural networks

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Chowdhury Rafeed Rahman, Preetom S. Arko, Mohammed Eunus Ali, Mohammad Ashik Iqbal Khan et al.

Journal: Biosystems EngineeringYear: 2020Citations: 542

Accurate and timely detection of diseases and pests in rice plants can help farmers in applying timely treatment on the plants and thereby can reduce the economic losses substantially. Recent developments in deep learning-based convolutional neural networks (CNN) have greatly improved image classifi...

Life SciencesAgricultural and Biological SciencesPlant ScienceOpen Access
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Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective

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A.K.M. Najmul Islam, Samuli Laato, Md. Shamim Talukder, Erkki Sutinen

Journal: Technological Forecasting and Social ChangeYear: 2020Citations: 530

Highlights • We study social media use, fake news sharing and social media fatigue during COVID-19.• Self-promotion and entertainment increase the sharing of unverified information.• Exploration and religiosity correlate negatively with the sharing of unverified information.• Deficient self-regulati...

Social SciencesSociology and Political ScienceMisinformation and Its ImpactsOpen Access
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A dynamic ensemble learning algorithm for neural networks

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Kazi Md. Rokibul Alam, Nazmul Siddique, Hojjat Adeli

Journal: Neural Computing and ApplicationsYear: 2019Citations: 527

This paper presents a novel dynamic ensemble learning (DEL) algorithm for designing ensemble of neural networks (NNs). DEL algorithm determines the size of ensemble, the number of individual NNs employing a constructive strategy, the number of hidden nodes of individual NNs employing a constructive–...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Transfer learning: a friendly introduction

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Asmaul Hosna, Ethel Merry, Jigmey Gyalmo, Zulfikar Alom et al.

Journal: Journal Of Big DataYear: 2022Citations: 523

Infinite numbers of real-world applications use Machine Learning (ML) techniques to develop potentially the best data available for the users. Transfer learning (TL), one of the categories under ML, has received much attention from the research communities in the past few years. Traditional ML algor...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization

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Tanvir Mahmud, Md Awsafur Rahman, Shaikh Anowarul Fattah

Journal: Computers in Biology and MedicineYear: 2020Citations: 523

With the recent outbreak of COVID-19, fast diagnostic testing has become one of the major challenges due to the critical shortage of test kit. Pneumonia, a major effect of COVID-19, needs to be urgently diagnosed along with its underlying reasons. In this paper, deep learning aided automated COVID-1...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Identification of significant features and data mining techniques in predicting heart disease

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Mohammad Shafenoor Amin, Yin Kia Chiam, Kasturi Dewi Varathan

Journal: Telematics and InformaticsYear: 2018Citations: 514
Health SciencesHealth ProfessionsHealth Information Management
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Meta-SR: A Magnification-Arbitrary Network for Super-Resolution

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Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang et al.

Year: 2019Citations: 503

Recent research on super-resolution has achieved great success due to the development of deep convolutional neural networks (DCNNs). However, super-resolution of arbitrary scale factor has been ignored for a long time. Most previous researchers regard super-resolution of differentscale factors as in...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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A Short-Term Load Forecasting Method Using Integrated CNN and LSTM Network

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Shafiul Hasan Rafi, Nahid‐Al Masood, Shohana Rahman Deeba, Eklas Hossain

Journal: IEEE AccessYear: 2021Citations: 489

In this study, a new technique is proposed to forecast short-term electrical load. Load forecasting is an integral part of power system planning and operation. Precise forecasting of load is essential for unit commitment, capacity planning, network augmentation and demand side management. Load forec...

Physical SciencesEngineeringElectrical and Electronic EngineeringOpen Access
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Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-Grained Image Recognition

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Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo

Year: 2019Citations: 488

Learning subtle yet discriminative features (e.g., beak and eyes for a bird) plays a significant role in fine-grained image recognition. Existing attention-based approaches localize and amplify significant parts to learn fine-grained details, which often suffer from a limited number of parts and hea...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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