Search Results - (("pattern _ algorithm") OR ((("self learning algorithm") OR ("pattern using algorithm"))))*
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1
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In this thesis the research of a self-learning algorithm will be presented, outlined and discussed in detailed manner. …”
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Thesis -
2
Education in the Era of IR 4.0
Published 2018“…IR 4.0 also known as the ‘digital revolution’: combines technological and human capacities in an unprecedented way through self- learning algorithms, self-driving cars, human–machine interconnection and big-data analytics.…”
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3
Two-wheel balancing robot; review on control methods and experiments
Published 2019“…This article intended to address the control methods of balancing two-wheeled mobile robot from linear controller, non-linear controller and adapting and self-learning algorithm. The focus of the review will be the evaluation and experiment done on two-wheel mobile robot. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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5
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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6
Identifying Relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm
Published 2013“…FP-Growth (Frequent Pattern) algorithm is employed for this purpose to generate itemsets given 0.2 (20%) as the support threshold value and 0.7 (70%) as the confidence value for association rule generation. …”
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Characterization of Pattern for Predicting Ultra Violet (UV) Effects in Environment Data Management System (EDMS)
Published 2013“…The result of the measurement exercises produced various patterns, each with unique identification for developing database pattern algorithm. Statistical analysis graph was plotted to justify the one year measurement of UV, temperature and humidity.…”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia
Published 2015“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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9
Finger Vein Recognition Using Pattern Map As Feature Extraction
Published 2012“…Since the low contrast finger vein images may contain shading and noise, it is important to precisely preprocess, extract and preserve the vein patterns. Algorithms such as Gabor Filter, Local Line Binary Pattern (LLBP) and Principal Component Analysis (PCA) have been proposed in recent study to extract finger vein features. …”
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10
Hilbert-peano and zigzag: Two approaches mapping pattern of digital watermarking for text images authentication
Published 2021“…We proposed a Zigzag SCAN pattern algorithm and compared it with the proposed Hilbert-Peano scheme. …”
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Class attendance management system using face recognition
Published 2018“…By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the Local Binary Patterns algorithm LBPs. If the student's input image matches withthetrained dataset image the prototype door will open using Servo Motor, then the attendance results will be stored in the MySQL database. …”
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Proceeding Paper -
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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