Search Results - (( java application tree algorithm ) OR ( framework implementation means algorithm ))
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Implementation of perez-dumortier calibration algorithm
Published 2014“…The implementation of the filtration procedure in step-by-step is discussed to render better framework of the proposed calibration algorithm. …”
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Chapter In Book -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Article -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Thesis -
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Real time monitoring and controlling using Petri net algorithm for batch process plant / Mohamad Shaiful Osman
Published 2010“…This thesis has presented a framework for designing and implementing a Petri net based supervisory for online control systems with the human in the loop, that mean human as a operator to switch the operation or monitoring the process flow. …”
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Thesis -
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Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications
Published 2017“…The experimental results show that the proposed framework produces better-quality and more accurate than normal flow state-of-the-art stereo matching algorithms. …”
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Article -
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Error concealment technique using wavelet neural network for wireless transmitted digital images
Published 2012“…Moreover, the concealment includes patches for both smooth and nonsmooth areas. This framework is implemented in three key steps. The first step is devoted to detecting invisible patches. …”
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Thesis -
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An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study
Published 2018“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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Thesis -
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Swarm intelligence (SI) algorithm is implemented because there are lot of previous works which prove that the SI is good for segmentation and classification. …”
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Thesis -
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Article -
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Embedded car plate image recognition system
Published 2008“…In order to speed up the image processing process, the system do not use complex algorithm such as Neural Network but use a simple algorithm such as template matching. …”
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Learning Object -
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An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…The model produced satisfactory performances even with a strict split of 50 %, confirming the high efficiency of the proposed framework. The mean Jaccard index and Dice similarity measures evaluated between the annotated and predicted mask ranged from 0.80 to 0.93 in the binary classification of pixels as “skin” versus “background”. …”
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The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning
Published 2025“…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
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Proceeding Paper -
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence
Published 2025“…In HMDB51 dataset, the proposed average detection accuracy of ST-GCN action recognition algorithm based on MediaPipe framework reaches 88.3%. …”
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Article -
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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