Search Results - (( data optimization method algorithm ) OR ( pattern classification cell algorithm ))
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1
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…A working classification algorithm is developed by using MATLAB and the Fuzzy Logic Toolbox to differentiate and classify the staining pattern of HEp-2 cell images. …”
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Final Year Project -
2
Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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Citation Index Journal -
3
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Conference or Workshop Item -
4
MITOTIC HEp-2 CELL RECOGNITION USING LOCAL BINARY PATTERN (LBP) AND k-NEAREST NEIGHBOUR (k-NN) CLASSIFIER
Published 2014“…This work aims to highlight the features of mitotic cells and to develop recognition algorithm for mitotic cell by incorporated Local Binary Pattern (LBP) and k-Nearest Neighbour to classified unlabelled image. …”
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Final Year Project -
5
Red blood cells classification with sharpening segmentation and mask R-CNN
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Conference or Workshop Item -
6
An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing
Published 2014“…The algorithm tested on the publicly available Mivia Hep-2 Cell image dataset. …”
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Final Year Project -
7
HEP-2 CELL FEATURE EXTRACTION USING WAVELET AND INDEPENDENT COMPONENT ANALYSIS
Published 2013“…Thus, this project will study on the technique to identify and classify the pattern of ANA automatically. Algorithms are created using MATLAB software and a Graphical User Interface (GUI) is generated for the algorithm to be easily used. …”
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Final Year Project -
8
Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images
Published 2019“…But, some structure of unnecessary cell accidently be removed such as small cell or damaged cell. …”
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Thesis -
9
FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES
Published 2013“…Next, to design an algorithm that can automatically identify the 2 patterns of the HEp-2 cell tested using ANA. …”
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Final Year Project -
10
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Resource competition part of AIRS poses another problem, here, premature memory cells are generated and therefore classification accuracy decreases. …”
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Thesis -
11
Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune
Published 2024thesis::master thesis -
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Thesis -
13
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Article -
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023“…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Thesis -
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Thesis -
18
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Conference or Workshop Item -
20
Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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