Search Results - (( processes specification method algorithm ) OR ( processes classification techniques algorithm ))

Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

“…An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…Statistical techniques such as Anisotropic Diffusion Filter (ADF), local contrast enhancement, and haze reduction in the CIELAB colour space, are incorporated in the proposed algorithms for the pre-processing step. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

“…The simulation results show that the computational efficiency of ERN and BPERN training process is highly enhanced when coupled with the proposed hybrid method.…”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

“…Sub-algorithms of SDW can be further divided into data pre-processing phase, specific tuning parameter selection, weight as additional variable, and exclusion of unwanted adjacency matrix. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The improvement process involved segmentation, feature selection and classification techniques. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

“…Based on literature review, automated identification of tropical freshwater algae is even non-existent yet, and this study is designed to fill this gap.The development process of the automated freshwater algae detection system involves with many techniques and computer methods such as image preprocessing,segmentation, feature extraction, and classification process by using ANN. …”
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Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

“…The proposed segmentation method shows higher sensitivity and specificity than other methods. …”
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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

“…Extraction; Feature extraction; Image denoising; Image segmentation; Classification technique; Feature extraction and classification; Feature extraction techniques; Features extraction; Images processing; Machine learning algorithms; Machine learning methods; Research areas; Sensory system; Visual sensory; Image classification…”

Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…This information can be processed, analyzed, and transformed into inputs for a decisional algorithm that controls the sprayer nozzle action in real-time. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

“…Data pre-processing method carries out certain computations such as data transformation (normalization, aggregation) to improve data quality. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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Classification of SNPs for obesity analysis using FARNeM modelling by Ong, Phaik Ling, Choo, Yun Huoy, Emran, Nurul Akmar

“…However, the overall analysis showed that, it is encouraging to include feature selection process before the learning algorithms.…”
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Framework for mining XML format business process log data by Ang, Jin Sheng

“…Therefore, a lot of frequent subtree mining (FSM) algorithms and methods were developed to get information from semi-structured data specifically data with hierarchical nature. …”
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The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems by Atomi, Walid Hasen

“…Specifically Min-Max, Z-Score and Decimal Scaling Normalization preprocessing techniques were evaluated. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.