Search Results - (( based extraction method algorithm ) OR ( related information learning algorithm ))*

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
Get full text
Get full text

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
Get full text
Get full text
Get full text
Get full text

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

“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
Get full text
Get full text

Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
Get full text
Get full text
Get full text
Get full text

Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…For overall, the back-propagation algorithm has been proved as a method that can be used for recognition areas.…”
Get full text
Get full text

Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…This study also suggests that transfer learning could improve the forecasting accuracy of the injury severity by nearly 10%.…”
Get full text
Get full text
Get full text

Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Retinal Microvascular Feature Extraction Using Faster Region-based Convolutional Neural Network by Mohammed Enamul, Hoque

“…The supervised CNN methods employ different algorithms that iteratively learn from data for analyzing data and predicting outcomes. …”
Get full text
Get full text

Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Daud, Muhamad Aliff Imran, Ahmad Puzi, Asmarani, Sidek, Shahrul Na'im, Zainuddin, Ahmad Anwar, Mohd Khairuddin, Ismail, Abd Mutalib, Mohd Azri

“…Muscle spasticity is always assessed by therapists using conventional methods involving passive movement and assigning spasticity grades to the relevant joints based on the degree of muscle resistance which leads to inconsistency in assessment and could affect the efficiency of the rehabilitation process. …”
Get full text
Get full text
Get full text

Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
Get full text
Get full text

Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Muhamad Aliff Imran, Daud, Asmarani Ahmad Puzi, asmarani@iium.edu.my, Shahrul Na’im, Sidek, Ahmad Anwar, Zainuddin, Ismail, Mohd Khairuddin, Mohd Azri, Abd Mutalib

“…Muscle spasticity is always assessed by therapists using conventional methods involving passive movement and assigning spasticity grades to the relevant joints based on the degree of muscle resistance which leads to inconsistency in assessment and could affect the efficiency of the rehabilitation process. …”
Get full text
Get full text
Get full text

Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance by Saidah Saad, Zikun, Huang

“…Named Entity Recognition (NER) is a crucial component in various domains, including medical and financial fields, as it helps identify text fragments belonging to predefined categories from unstructured text. Over time, NER algorithms have evolved from dictionary-based approaches to machine learning and deep learning techniques. …”
Get full text
Get full text
Get full text

Content-based indexing of low resolution documents by Md Nor, Danial

“…The algorithm has the capability of reducing any shortcoming associated with normalisation in initial fusion technique. …”
Get full text
Get full text
Get full text
Get full text

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…Accordingly, the aim of this study is to identify the latest SQL injection attacks based on user’s inputs in web application associated with remote server database, and to develop a new method based on dynamic detection technique to prevent SQL injection attacks. …”
Get full text
Get full text
Get full text

Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…This thesis proposes a hybrid indoor positioning method for single base station systems by jointly utilizing the fingerprinting method and geometric multilateration. …”
Get full text
Get full text

Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…The proposed BANN model achieved the best training accuracies of (95%) and best prediction accuracies of (92%) based on testing data compared to other employed methods. …”
Get full text
Get full text

A block-based multi-scale background extraction algorithm by Davarpanah, Seyed Hashem, Khalid, Fatimah, Golchin, Maryam

“…Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. …”
Get full text
Get full text

Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…Recently, considerable advancement has been achieved in semi-supervised multi-task feature selection algorithms, where they have exploited the shared information from multiple related tasks. …”
Get full text
Get full text
Get full text