Search Results - (( java segmentation using algorithm ) OR ( pattern solution learning algorithm ))
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1
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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2
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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3
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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4
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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5
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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Article -
6
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Proceeding Paper -
7
Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Working Paper -
8
Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Final Year Project / Dissertation / Thesis -
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Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi
Published 2024“…This research aims to improve the detection and analysis of cracks on concrete surfaces by utilizing UAVs and yolo algorithms. Uavs offer a versatile and cost-effective solution for capturing high-resolution orthophotos of large and hard-to-reach concrete structures. …”
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Student Project -
10
Concrete surface inspection by using Unmanned Aerial Vehicle (UAVs) and deep learning algorithms Yolov7
Published 2024“…This research aims to evaluate the detection and analysis of cracks on concrete surfaces by utilizing Uavs and Yolo algorithms. Uavs offers a versatile and cost-effective solution for capturing high-resolution orthophotos of large and hard-to-reach concrete structures. …”
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Conference or Workshop Item -
11
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
12
Underwater Image Recognition using Machine Learning
Published 2024“…It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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13
Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki
Published 2024“…Further enhancements might involve including machine learning algorithms to improve the prototype's accuracy by learning from a larger dataset, which would eventually improve the prototype's ability to offer deep understanding into handwriting patterns related to dyslexia.…”
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14
Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar
Published 2012“…Many algorithms have been applied to aid the assessment process. …”
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Research Reports -
15
Adaptive security architecture for protecting RESTful web services in enterprise computing environment
Published 2018“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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16
Adaptive security architecture for protecting RESTful web services in enterprise computing environment
Published 2018“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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17
Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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18
Application of machine learning and artificial intelligence in detecting SQL injection attacks
Published 2024“…Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored, these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions, with some algorithms scoring up to an 80 percent success rate in identifying SQL injections. …”
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19
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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20
New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
Published 2024“…Traditional single machine learning models struggle to capture complex temporal patterns, especially considering the influence of vaccination campaigns on confirmed cases, leading to suboptimal predictions. …”
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