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Field: Anomaly Detection Techniques and Applications

Multi-Person Pose Estimation With Enhanced Channel-Wise and Spatial Information

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Kai Su, Dongdong Yu, Zhenqi Xu, Xin Geng et al.

Year: 2019
Citations: 171

Multi-person pose estimation is an important but challenging problem in computer vision. Although current approaches have achieved significant progress by fusing the multi-scale feature maps, they pay little attention to enhancing the channel-wise and spatial information of the feature maps. In this...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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Support Vector Machine and Random Forest Modeling for Intrusion Detection System (IDS)

Verified

Md. Al Mehedi Hasan, Mohammed Nasser, Biprodip Pal, Shamim Ahmad

Journal: Journal of Intelligent Learning Systems and ApplicationsYear: 2014Citations: 169

The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with many features. To get rid of this problem, several types of intrusion detection methods have been proposed and shown different lev...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Improving accuracy of students’ final grade prediction model using optimal equal width binning and synthetic minority over-sampling technique

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Syed Tanveer Jishan, Raisul Islam Rashu, Naheena Haque, Rashedur M. Rahman

Journal: Decision AnalyticsYear: 2015Citations: 168

Abstract There is a perpetual elevation in demand for higher education in the last decade all over the world; therefore, the need for improving the education system is imminent. Educational data mining is a newly-visible area in the field of data mining and it can be applied to better understanding ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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An adaptive ensemble classifier for mining concept drifting data streams

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Dewan Md. Farid, Li Zhang, Alamgir Hossain, Chowdhury Mofizur Rahman et al.

Journal: Expert Systems with ApplicationsYear: 2013Citations: 167
Physical SciencesComputer ScienceArtificial Intelligence
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Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection

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Dewan Md Singh, Nouria Harbi, Mohammad Zahidur Rahman

Journal: International Journal of Network Security & Its ApplicationsYear: 2010Citations: 166

in the last decades. However, there remain various issues needed to be examined towards current intrusion detection systems (IDS). We tested the performance of our proposed algorithm with existing learning algorithms by employing on the KDD99 benchmark intrusion detection dataset. The experimental r...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Dependable Intrusion Detection System for IoT: A Deep Transfer Learning Based Approach

Verified

Sk. Tanzir Mehedi, Adnan Anwar, Ziaur Rahman, Kawsar Ahmed et al.

Journal: IEEE Transactions on Industrial InformaticsYear: 2022Citations: 162

Security concerns for Internet of Things (IoT) applications have been alarming because of their widespread use in different enterprise systems. The potential threats to these applications are constantly emerging and changing, and, therefore, sophisticated and dependable defense solutions are necessa...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers

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Prottoy Saha, Muhammad Sheikh Sadi, Md. Milon Islam

Journal: Informatics in Medicine UnlockedYear: 2020Citations: 161

Recently, coronavirus disease (COVID-19) has caused a serious effect on the healthcare system and the overall global economy. Doctors, researchers, and experts are focusing on alternative ways for the rapid detection of COVID-19, such as the development of automatic COVID-19 detection systems. In th...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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AutoML: A systematic review on automated machine learning with neural architecture search

Verified

Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S. M. Noman et al.

Journal: Journal of Information and IntelligenceYear: 2023Citations: 155

AutoML (Automated Machine Learning) is an emerging field that aims to automate the process of building machine learning models. AutoML emerged to increase productivity and efficiency by automating as much as possible the inefficient work that occurs while repeating this process whenever machine lear...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Deep Learning Based Systems Developed for Fall Detection: A Review

Verified

Md. Milon Islam, Omar Tayan, Md. Repon Islam, Md. Saiful Islam et al.

Journal: IEEE AccessYear: 2020Citations: 145

Accidental falls are a major source of loss of autonomy, deaths, and injuries among the elderly. Accidental falls also have a remarkable impact on the costs of national health systems. Thus, extensive research and development of fall detection and rescue systems are a necessity. Technologies related...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks

Verified

Sk. Tanzir Mehedi, Adnan Anwar, Ziaur Rahman, Kawsar Ahmed

Journal: SensorsYear: 2021Citations: 142

The Controller Area Network (CAN) bus works as an important protocol in the real-time In-Vehicle Network (IVN) systems for its simple, suitable, and robust architecture. The risk of IVN devices has still been insecure and vulnerable due to the complex data-intensive architectures which greatly incre...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities

Verified

Md Golam Morshed, Tangina Sultana, Aftab Alam, Young-Koo Lee

Journal: SensorsYear: 2023Citations: 139

Human action recognition systems use data collected from a wide range of sensors to accurately identify and interpret human actions. One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-base...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Application of Machine Learning Approaches in Intrusion Detection System: A Survey

Verified

Nutan Farah, Md. Avishek, Faisal Muhammad, Abdur Rahman et al.

Journal: INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ARTIFICIAL INTELLIGENCEYear: 2015Citations: 139

Network security is one of the major concerns of the modern era. With the rapid development and massive usage of internet over the past decade, the vulnerabilities of network security have become an important issue. Intrusion detection system is used to identify unauthorized access and unusual attac...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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LSCP: Locally Selective Combination in Parallel Outlier Ensembles

Verified

Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki, Zheng Li

Journal: Society for Industrial and Applied Mathematics eBooksYear: 2019Citations: 138

In unsupervised outlier ensembles, the absence of ground truth makes the combination of base outlier detectors a challenging task. Specifically, existing parallel outlier ensembles lack a reliable way of selecting competent base detectors, affecting accuracy and stability, during model combination. ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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A Critical Review of Artificial Intelligence Based Approaches in Intrusion Detection: A Comprehensive Analysis

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Salman Muneer, Umer Farooq, Atifa Athar, Muhammad Ahsan Raza et al.

Journal: Journal of EngineeringYear: 2024Citations: 136

Intrusion detection (ID) is critical in securing computer networks against various malicious attacks. Recent advancements in machine learning (ML), deep learning (DL), federated learning (FL), and explainable artificial intelligence (XAI) have drawn significant attention as potential approaches for ...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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A reliable Internet of Things based architecture for oil and gas industry

Verified

Wazir Zada Khan, Mohammed Y. Aalsalem, Muhammad Khurram Khan, Md. Shohrab Hossain et al.

Year: 2017Citations: 115

Anomaly detection systems deployed for monitoring in oil and gas industries are mostly WSN based systems or SCADA systems which all suffer from noteworthy limitations. WSN based systems are not homogenous or incompatible systems. They lack coordinated communication and transparency among regions and...

Physical SciencesComputer ScienceComputer Networks and Communications
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