Search Results - evolution ((detection techniques) OR (((mining techniques) OR (learning techniques))))

Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. The evolution of authoritative immunofingerprint mining technology is exerting a growing influence on comprehensive cancer diagnosis biology. …”
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Global Trends of Educational Data Mining in Online Learning by Chen, Chwen Jen, Teh, Chee Siong, Dexter Sigan, John

“…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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Data mining in computer auditing / Hiromi Wong, Siew Lan and Valery Fred Lee by Hiromi , Wong, Siew , Lan, Valery, Fred Lee

“…The report will cover the literature review that started with an introduction to computer auditing, introduction to data mining, data mining techniques (classification, neural network and sequential analysis), and the existing data mining software. …”
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Critical review of object detection techniques for traffic light detection in intelligent transportation systems by Muhammad Adhwa, Mohd Salemi, Muhammad Arif, Mohamad

“…This study provides a critical review of object detection techniques specifically for traffic light detection, evaluating the evolution of machine learning frameworks, deep learning architectures, and hybrid optimization models. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…In this work, a new islanding detection technique is proposed based on combination of Slantlet Transform and Ridgelet Probabilistic Neural Network to detect islanding conditions from other disturbance for a 250-kW PV array connected to a typical North American distribution grid and a wind farm power generation system. …”
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Global trends of educational data mining in online learning by Nie Hui Ling, Chwen Jen Chen, Chee Siong Teh, Dexter Sigan John, Looi Chin Ch’ng, Yoon Fah Lay

“…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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Comparison of detection model using machine learning on android malware / Muhammad Ikmal Ihsan by Ihsan, Muhammad Ikmal

“…This project utilized supervised machine learning techniques such as SVMs, Naive Bayes and Random Forest to build an android malware detection model. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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Driving fatigue detection system using haar cascade technique by Davanathan, Sasmita, Md Taujuddin, Nik Shahidah Afifi, Suhaila Sari, Suhaila Sari

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Object detection and classification using few-shot learning in smart agriculture: A scoping mini review by Nitiyaa Ragu, Jason Teo

“…One of the techniques that is popular is Few-Shot Learning (FSL). …”
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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

“…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

“…In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. …”

Enhanced Parallel Deep Learning for Malware Detection (EPDL-MD) Model by Madihah Mohd Saudi, Chowdhury Sajadul Islam, Nur Hafiza Zakaria

A joint learning classification for intent detection and slot filling from classical to deep learning: a review by Muhammad Yusuf, Idris, Naomie, Salim, Anazida, Zainal, Sinarwati, Mohamad Suhaili

“…This study explores the evolution of joint learning models for intent detection and slot filling from 2008 to 2024, covering both classical and deep learning approaches. …”
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A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

“…One of the most dynamic areas in AI research is object detection, a field that continues to evolve due to advancements in chip computing power and deep learning techniques. …”
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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…However, in this project, deep learning techniques are used in developing a model for diseases and pest detection in plants, and then train and test the model before eventually integrating the model into a mobile application. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S. M. M Yassin, S. M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry.The malicious software which is specifically designed to disrupt,damage,or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective.To solve the problem,this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately.The integrated classifier algorithm applied to examine,classify and generate rules of the pattern and program behaviour of system call information.The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S.M.M Yassin, S.M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…To solve the problem, this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately. …”
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Overview and future opportunities of sentiment analysis approaches for big data by Mohd Sharef, Nurfadhlina, Mat Zin, Harnani, Nadali, Samaneh

“…The contribution of this paper is two-fold: (i) this study reviews the state of the art of SA approaches. including sentiment polarity detection, SA features (explicit and implicit), sentiment classification techniques and applications of SA and (ii) this study reviews the suitability of SA approaches for application in the big data frameworks, as well as highlights the gaps and suggests future works that should be explored. …”
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Deep learning-enhanced jewelry material jadeite jade quality assessment by Meng, Liang, Raja Ahmad Effendi, Raja Ahmad Azmeer, Sun, Wei, Mo, Lili, Abdul Rahman, Ahmad Rizal, Hsu, Yu-Lin, Barron, Deirdre

“…Jadeite jade, renowned for its unique texture and cultural significance, stands as the epitome of jade varieties, embodying the latest evolution of China’s jade culture. This research endeavors to establish an AI model for precisely screening jadeite quality, employing deep learning techniques to revolutionize jadeite design and detection. …”
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