Search Results - (( initial detection method algorithm ) OR ( using classification using algorithm ))

A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

“…This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. …”
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Attacks detection in 6G wireless networks using machine learning by Saeed, Mamoon M., Saeed, Rashid A., Gaid, Abdulguddoos S. A., Mokhtar, Rania A., Khalifa, Othman Omran, Ahmed, Zeinab E.

“…The proposed method shown an outperformed the existing classification method. …”
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Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

“…Once the initial classification is performed using the generalized rules for each test example, the results are validated using the experts feedback. …”
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Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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Development of Scoliotic spine severity detection using deep learning Algorithms by Makhdoomi, Nahid Ameer, Gunawan, Teddy Surya, Idris, Nur Hanani, Khalifa, Othman Omran, Karupiah, Rajandra Kumar, Bramantoro, Arif, Abdul Rahman, Farah Diyana, Zakaria@Mohamad, Zamzuri

“…Using Convolutional Neural Network (CNN), this research will integrate an artificial intelligence-assisted method for detecting and classifying Scoliosis illness types. …”
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Early bacterial detection in bloodstream infection using deep transfer learning algorithm by Son Ali, Akbar, Kamarul Hawari, Ghazali, Habsah, Hasan, Wahyu Sapto, Aji, Yudhana, Anton

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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Fuzzification of epileptic data: an application for prediction and identification of partial seizure by Malik, Aamir Saeed, Nasif, Mohammad Shakir, Kamel , Nidal, Qidwai, U.

“…Method: Due to the compact nature of ubiquitous systems, the detection and classification techniques have to be extremely simple work in real-time. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

“…Initially, one set of sensor data, features or classifiers were used for activity recognition applications. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

“…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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How can unmanned aerial vehicles be used for detecting weeds in agricultural fields? by Mohidem, Nur Adibah, Che’Ya, Nik Norasma, Juraimi, Abdul Shukor, Fazlil Ilahi, Wan Fazilah, Mohd Roslim, Muhammad Huzaifah, Sulaiman, Nursyazyla, Saberioon, Mohammadmehdi, Mohd Noor, Nisfariza Maris

“…Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. …”
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How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields? by Nur Adibah Mohidem, Nik Norasma Che’Ya, Abdul Shukor Juraimi, Wan Fazilah Fazlil Ilahi, Muhammad Huzaifah Mohd Roslim, Nursyazyla Sulaiman, Mohammadmehdi Saberioon, Nisfariza Mohd Noor

File integrity monitor scheduling based on file security level classification by Abdullah, Zul Hilmi, Udzir, Nur Izura, Mahmod, Ramlan, Samsudin, Khairulmizam

“…File integrity monitoring tools are widely used to detect any malicious modification to these critical files. …”
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”

An implementation of regional descriptor and line roi in development of semi-automated strabismus detection system by Zolkifli, Nur Syazlin

“…Initially, the image in pre-processing undergoes Viola Jones algorithm, red channel extraction, contrast adjustment and median filtering to reduce the noise and enhance the image. …”
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Drone-based surveillance of palm tress ecosystems by Mansor, Ya’akob, Baki, Sharudin Omar, Sahwee, Zulhilmy, Mengyue, Cheng, Wu, Yuanyuan

“…The initial phase of the research focuses on elucidating the challenges associated with detecting palm tree health issues using conventional image processing methods in MATLAB. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…Unlike traditional methods that usually start with detection and followed by denoising, the model initially leverages the powerful ability of deep CNN architecture to separate noise from noisy image, then adopts PSO to pinpoint the most optimized threshold values for detecting impulse noisy pixels. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

“…The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. …”
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