Search Results - (( basic learning issues algorithm ) OR ( java implementation drops algorithm ))
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…It is found that the interrelated tasks in the programming process, with its various abstractions, and timing in delivering the feedback, need to be addressed with the equal attention in learning to program. Taking into account from those main issues, this study introduces the new model of integrated algorithm-program visualization (ALPROV) for developing program comprehension tool. …”
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Email spam classification based on deep learning methods: A review
Published 2025“…The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. …”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review
Published 2024“…The main challenges highlighted are regarding the ethical issues of the data available. Furthermore, it is also shown that various machine learning algorithms are used, and the most used are Neural Network and Support Vector Machine. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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A study on personalized recommender system using social media
Published 2020“…The evaluation on these algorithm is done to evaluate accuracy of the algorithm. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Review and bibliometric analysis of AI-driven advancements in healthcare
Published 2024“…Research shows that "algorithm", "machine learning", "deep learning", "controlled study", "major clinical study" and "healthcare delivery" as well as "decision support systems" are key topics for research. …”
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A review of Convolutional Neural Networks in Remote Sensing Image
Published 2019“…Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. …”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Furthermore, using the basic features, TLSMalDetect achieved the highest accuracy of 93.69% by Naïve Bayes (NB) among the ML algorithms applied. …”
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A deep learning approach: The impact of sentiment analysis of Bangladeshi workers over the world
Published 2025“…TF-IDF vectorization was used for feature extraction, followed by basic machine learning algorithms such as Decision Tree, Support Vector Machine, and Naive Bayes. …”
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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
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Text-based emotion prediction system using machine learning approach
Published 2020“…Several market challenges facing in the advancement of emotion analysis with accuracy being the main issue. Therefore, four supervised machine learning classification algorithms such as Multinomial Naïve Bayes, Support Vector Machine, Decision Trees, and kNearest Neighbors were investigated. …”
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The design for antrophomorphic sociable agent interaction through emotion detection
Published 2003“…This research works addresses on faces features through simulation of anthropomorphic agent.A salience feature of this definition of emotion is described in terms of goals and roles.Therefore, it provides a basic framework of goal-driven processing, which is to investigate computational models of emotion.The main goal of this research is to provide a natural interaction scheme where the affective interaction emotive state of the user can be identified.One aspect of developing such a capability is the ability of the system to recognize emotional state using intelligent supervised learning algorithms, personality of the user and respond appropriately.An anthropomorphic agent will serve to express the reaction through affective feedback given. …”
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