Search Results - evolution ((computing techniques) OR (learning techniques))

Modeling 2D appearance evolution for 3D object categorization by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

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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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Assistive Technology For Disabilities: A Case Study Of Autism In Teaching And Learning Outcomes by Omar, Sarah, Bidin, Azman, Koo, Ah Choo

“…A number of studies have highlighted new teaching techniques. There has been a trend in moving towards e-learning technologies in (Agarwal, 2012) and (Kemp, 2015), where those strategies were part of pedagogy techniques in teaching children with special needs. …”
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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Addressing these OBL limitations, this research proposes a new general OBL technique inspired by a natural phenomenon of parallel mirrors systems called the Parallel Mirrors Technique (PMT). …”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development by Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.

“…This review uniquely focuses on harnessing the synergy between ML and computational modeling (CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction (HER) catalysts and various hydrogen production processes (HPPs). …”

Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review by Hashmani, M.A., Jameel, S.M., Rehman, M., Inoue, A.

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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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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Japanese computer-aided learning package / Siti Nur Hidayah Johar by Siti Nur Hidayah , Johar

“…NihonGo was developed using incremental evolution through rapid prototyping technique. The development tool used include Visual Basic.NET, Microsoft Access 2003, Adobe Photoshop CS, and Macromedia Flash MX 2004 and so on. …”
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Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review by Zulkifli, Mansor, Irawan, Addie, Mohammad Fadhil, Abas

“…The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. …”
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A review of recent usability measures in English Language Teaching (ELT) technologies by Cheng L.K., Puteh F., Selamat A., Mohamed F.B.

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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From tiny-AI to lite-AI in edge computing by MD Ali, Mohd Adli

“…This approach enhances their functionality while maintaining computational efficiency. Various techniques, such as mixed learning, are employed to ensure maximum efficiency. …”
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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 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

“…It discusses the limitations of classical models, which led to the rise of deep learning techniques, and introduces a new taxonomy for joint learning classifying joint learning architectures. …”
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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. …”

Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

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Comparison of detection model using machine learning on android malware / Muhammad Ikmal Ihsan by Ihsan, Muhammad Ikmal

“…The result of the comparison using the machine learning techniques for Android malware dataset discovered that SVM machine learning get the highest percentage with accuracy of 0.93. …”
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Enhanced Parallel Deep Learning for Malware Detection (EPDL-MD) Model by Madihah Mohd Saudi, Chowdhury Sajadul Islam, Nur Hafiza Zakaria