Search Results - (( process classification model algorithm ) OR ( variable extraction method algorithm ))

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…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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A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

“…In this paper, an adaptive model for smile classification is suggested that integrates a row-transform-based feature extraction algorithm and a cascade classifier to increase the precision of facial recognition. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

“…In this research, Object-Based Image Analysis (OBIA) method was applied on hyperspectral data to extract the crown of individual tree species for classification and estimation purposes. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…The backscattering value of each tree was then extracted from the ALOS PALSAR-2 image. Using the Extract Multi Values tool in ArcGIS, the backscattering value for each oil palm point was derived from the processed ALOS PALSAR-2 image. …”
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Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
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Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…If the datasets contains irrelevant features, it will not only affect the training of the classification process but also the accuracy of the model. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

“…Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…For this purpose, the dataset was randomly split into three sets, 60.0% for model training, 20.0% for model validating, and 20.0% for model testing. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

“…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

“…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

“…Feature selection or attribute reduction is a crucial process to achieve optimal data reduction for classification task. …”
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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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