Search Results - (( java segmentation using algorithm ) OR ( missing learning selection algorithm ))

Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

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An adaptive opposition-based learning selection: The case for jaya algorithm by Nasser, Abdullah B., Kamal Z., Zamli, Hujainah, Fadhl, Ghanem, Waheed Ali H. M., Saad, Abdul-Malik H. Y., Mohammed Alduais, Nayef Abdulwahab

“…Over the years, opposition-based Learning (OBL) technique has been proven to effectively enhance the convergence of meta-heuristic algorithms. …”
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

“…The main problem in robotic system is in selecting the correct behaviour. The aim of this research is to overcome the behaviour selection problem. …”
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Human odour detection approach using machine learning by Ahmed Qusay Sabri

“…The unsurpassed framework for learning algorithm to be used for human identification is Levenberg-Marquardt backpropagation learning algorithm. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…Then different features are derived from the segmented region using Gray Intensity Co-Occurrence Distribution Matrix (GICDM) which is processed by applying a proposed Supervised Jaya Optimized Rough Set based Feature Selection (SJORSFS) algorithm. These algorithms select the best features according to the fitness value, and its redundancy is to be reduced. …”
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi

“…The first step was to smooth out the data by using a filtering technique namely Savitzky-Golay to eliminate the noise of the spectrum. In order to select the most significant wavelengths, genetic algorithm (GA) was used as a forward feature selection technique. …”
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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Missing data is a pervasive challenge in diverse datasets, often resulting from human error, system faults, and respondent non-response. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

Predicting Breast Cancer Intelligently with Machine Learning Techniques by Manimozhi, I., Laksmi, D.

“…Multiple machine learning algorithms, such as Support Vector Machine (SVM), Random Forest, Naïve Bayes, Logistic Regression, and K-Nearest Neighbors (KNN), are implemented and compared. …”
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Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model by Kareem Thajeel, Isam, Samsudin, Khairulmizam, Hashim, Shaiful Jahari, Hashim, Fazirulhisyam

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Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

“…In both versions, feature selection was done along with hyperparameter tuning to have a better performance for both models. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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