Search Results - (( evolution activation function algorithm ) OR ( learning application interface algorithm ))
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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2
VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. …”
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3
Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
4
An improved grey wolf with whale algorithm for optimization functions
Published 2022“…The performance of the proposed algorithm is tested and evaluated on five benchmarked unimodal and five multimodal functions. …”
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Automatic email classification system / Phang Siew Ting
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Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
Published 2022“…Next, the adaptive initial contour (AIC), δ, and stopping function were integrated to create the adaptive Chan-Vese active contour (ACVAC) algorithm. …”
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Article -
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A Machine Learning Classification Application to Identify Inefficient Novice Programmers
Published 2023“…Data mining; Graphical user interfaces; Learning algorithms; Machine learning; Nearest neighbor search; Academic performance; Application layers; Computer science students; Educational data mining; Educational Institutes; K-near neighbor; Machine learning classification; Nearest-neighbour; Novice programmer; Productive tools; Students…”
Conference Paper -
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Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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10
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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11
A new mobile botnet classification based on permission and API calls
Published 2024Subjects:Conference Paper -
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Fast Corner Detection in Augmented Reality Learning Management of the Corpse
Published 2021“…The application also meets 82.8% of the user side's usability level, which indicates that this application is beneficial for learning. …”
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Journal -
14
Segmentation of Retinal Vasculature using Active Contour Models (Snakes)
Published 2009“…The detection of the retinal vessel is achieved by performing image enhancement using CLAHE followed by Bottom-hat morphological transformation. Active contour model (snake) that based on level sets, techniques of curve evolution, and Mumford-Shah functional for segmentation is then used to segment out the detected retinal vessel and produce a complete retinal vasculature. …”
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Final Year Project -
15
Development of deep learning based user-friendly interface for fruit quality detection
Published 2024“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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Article -
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Algorithm visualization design guidelines for mobile leaning
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Affective computation on EEG correlates of emotion from musical and vocal stimuli
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Proceeding Paper -
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Classification of multichannel EEG signal by single layer perceptron learning algorithm
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Proceeding Paper -
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NLP- based for providing mental health support in mobile application / Muhammad Amirul Roslan
Published 2025“…Future enhancements, such as advanced machine learning algorithms and user interface improvements, are proposed to further enhance functionality. …”
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Thesis -
20
A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”
Proceedings Paper
