Search Results - (( _ constructive method algorithm ) OR ( data visualization learning algorithm ))
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…This study addresses the urgent issue of detecting hidden defects in semiconductor wafers that conventional methods overlook. This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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Machine learning application for concrete surface defects automatic damage classification
Published 2024“…This model is trained using 80% of the image data and tested using another 20% of the image data. …”
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Application of target detection method based on convolutional neural network in sustainable outdoor education
Published 2023“…Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. …”
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Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper -
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…K-Nearest Neighbour (KNN) is a well-known incremental learning method which applies First-In-First-Out (FIFO) knowledge update strategy. …”
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Mean of correlation method for optimization of affective states detection in children
Published 2018“…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
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Algorithm visualization design guidelines for mobile leaning
Published 2018“…This study is about the algorithm visualization design guidelines for mobile platform, to teach students data structures and algorithm (DSA) subject effectively. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2022“…This paper analyzed several visual analytics approaches instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper -
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Designing algorithm visualization on mobile platform: The proposed guidelines
Published 2017“…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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A hybrid spiking neural network model for multivariate data classification and visualization.
Published 2011“…This study proposes a hybrid model of Self-Organizing Map with modified adaptive coordinates (SOM-AC) and Spiking Neural Network (SNN) for multivariate spatial and temporal data visualization and classification. SOM is one of the most prominent unsupervised learning algorithms. …”
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A review on monocular tracking and mapping: from model-based to data-driven methods
Published 2022“…Astounding results from early methods based on filtering have intrigued the community to extend these algorithms using other forms of techniques like bundle adjustment and deep learning. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Final Year Project Report / IMRAD -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset
Published 2018“…In hydrology especially, every process is unique and dependent on large number of natural factors hence modelling using machine learning algorithm without considering hydrological insight is very dangerous. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper
