Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

“…Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). …”

Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array by Amran Hossain (570706)

“…Later, a nine-antenna array-based microwave brain imaging (MBI) system is implemented and investigated by using phantom model. After that, the scattering parameters are collected, analyzed, and then processed by the Iteratively Corrected delay-multiply-and-sum algorithm to detect and reconstruct the brain tumor images. …”

Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”

Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

“…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …”

Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya Saleh (18520026)

“…Computer-Aided Detection (CAD) has been used to process CT images of the lung to determine whether an image has traces of cancer. …”

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…A dataset publicly available for a smart home, along with weather conditions, is used for the methodology validation. The proposed algorithm is used to detect the spamicity score of the connected IoT devices in the network. …”

Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…The Extended Kalman Filter (EKF) is used for state estimation with proper clutter and detection models. …”
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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…In this paper, the feasibility of satellite remote sensing in detecting and predicting locations of buried objects in the archaeological site of Saruq Al-Hadid, United Arab Emirates (UAE) was investigated. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben-Romdhane, Haïfa

“…In this paper, the feasibility of satellite remote sensing in detecting and predicting locations of buried objects in the archaeological site of Saruq Al-Hadid, United Arab Emirates (UAE) was investigated. …”
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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

HVAC system attack detection dataset by Mariam Elnour (14147790)

“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”

Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks by Ioannis A. Tsalafoutas (14776939)

“…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”

Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. In order to detect the anomalies in a dataset in an unsupervised manner, some novel statistical techniques are proposed in this paper. …”

A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation by Sawas, Abdullah M.

“…A multistage approach to passive islanding detection is proposed that utilizes a decision tree (DT) like classification algorithm. …”
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