Search Results - (( java application model algorithm ) OR ( using function learning algorithm ))
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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil
Published 2024“…This research will focus only on six basic baby sign languages that are commonly used in daily life. The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Provider independent cryptographic tools
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Monograph -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Real-time algorithmic music composition application.
Published 2022“…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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Final Year Project / Dissertation / Thesis -
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
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Training functional link neural network with ant lion optimizer
Published 2020“…Functional Link Neural Network (FLNN) has becoming as an important tool used in machine learning due to its modest architecture. …”
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Conference or Workshop Item -
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Direct approach for mining association rules from structured XML data
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Thesis -
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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Final Year Project -
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Secure Image Steganography Using Encryption Algorithm
Published 2016“…The objective of this study is to enhance the confidentiality and security of the image steganography application by combining cryptography algorithm. In this proposed model, the RSA algorithm is used to encrypt a secret message into an unreadable ciphertext before hiding it in the image. …”
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Conference or Workshop Item -
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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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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Thesis -
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Dynamic training rate for backpropagation learning algorithm
Published 2013“…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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Conference or Workshop Item -
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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