Search Results - (( using combination using algorithm ) OR ( basic classification modeling algorithm ))
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Disposable Biomimetic Array Sensor Strip Coupled With Chemometric Algorithm For Quality Assessment Of Orthosiphon Stamineus Benth Samples
Published 2006“…The classification model built with PCA was useful for the discrimination of the herb according to its parts; stem and leaves, while was also successfully applicable for different type of O.stamineus extracts identification. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia
Published 2021“…The Random Forest (RF) algorithm was used to classify the land use land cover (LULC) with 222 training samples and 78 verification samples obtained through the Google Earth Pro higher resolution satellite images and field samplings. …”
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…A 1.4 second processing time was achieved when the combination was applied on ROI2 for the Virescens colour model. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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A Novel Method for Fashion Clothing Image Classification Based on Deep Learning
Published 2023“…In actual experiments, the classification accuracy of the suggested method was 93 percent, 4.6 percent higher than that of the basic CNN model. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The derived model was rigorously compared to four models, including basic ELM, basic FLN, Reduce Kernel ELM (RK-ELM), and RK-FLN. …”
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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Proceeding Paper -
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Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf
Published 2015“…This indicates that the proposed algorithm is not suitable to be used as AMPs predictor. …”
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EMG motion pattern classification through design and optimization of Neural Network
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…Thus, this research is aimed to develop two models. First, the BrC detection model is developed to diagnose BrT basic types like benign and malignant. …”
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Review of deep convolution neural network in image classification
Published 2017“…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
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Modelling of clinical risk groups (CRGs) classification using FAM
Published 2006“…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…With the trained and tuned CNN model, a cross-database classification evaluation is carried out. …”
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Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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