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How Does Image Complexity Affect the Accuracy of an Interactive Image Segmentation Algorithm?
Published 2025“…The adaptive strategy improves segmentation performance and guides the development of robust algorithms. Future research can further refine the adaptive approach, explore additional complexity measures, and incorporate advanced machine learning techniques to enhance interactive image segmentation. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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The impact of virtual reality on programming algorithm courses on student learning outcomes
Published 2024“…This study aims to determine the impact of VR compared to traditional learning in improving student learning outcomes on programming algorithm materials. …”
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Software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm
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Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
Published 2019“…Pairwise test design technique is found useful by testers to sample only required configuration options of these systems for exploring errors owing to their interactions. Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
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Kodepoly: an engaging approach to blended futuristic learning in coding
Published 2024“…By combining the strategic elements of Monopoly with a curriculum comprised of coding challenges, debugging exercises, and algorithmic puzzles, Kodepoly aims to render the learning process both enjoyable and substantial in content. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
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Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood
Published 2015“…Imitation learning through self-exploration is essential in development of sensorimotor skills in infants. …”
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Hyper-heuristic strategy for input-output-based interaction testing
Published 2022“…Classical test case design strategies, however, do not sufficiently include support for exploration of faults due to interaction between parameter values. …”
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Statistics Easy Tool (SET) / Noor Aisyah Idris and Nurdia Azlin Ghazali
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…The use of meta-heuristic algorithms as the basis for t-way (where t indicates the interaction strength) and mixed strength testing strategies is common in recent literature. …”
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Using Pattern Matching technique for feature recognition of STEP file
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Harnessing reinforcement learning in fog-cloud computing: challenges, insights, and future directions
Published 2024“…This article explores the different RL algorithms, emphasizing their distinct strengths, weaknesses, and practical implications in fog-cloud environments. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…A metaheuristic is defined as an iterative generation process which guides a subordinate heuristic through a combination of different intelligent concepts for exploring and exploiting the solution space; they employ learning strategies to structure information in order to establish efficient near-optimal solutions. …”
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