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13 results for “Comparing Learning Algorithms”

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Research ArticleOpen accessIn the keywordsMapping Learning Algorithms on Data, a Useful Step for Optimizing Performances and Their ComparisonFilippo NeriIn this paper, we propose a novel methodology to map learning algorithms on data (performance map) in order to gain more insights into the distribution of their performances across their parameter space. This methodology provides useful information when selecting a learner's best configuration for the data at hand and it also enhances the comparison of learners across learning contexts. In … …Journal of Computer Science, Vol. 20, Issue 9 · 10 Jul 2024 · 4,501 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Lightweight PyBullet-Based Framework for Fast Reinforcement Learning Prototyping on 6-DOF Robotic ArmsNgoc Kim Khanh Nguyen, Anh Thu Mang, Quang NguyenControlling 6-Degree-of-Freedom (6-DOF) robotic arms for precise manipulation tasks is challenging due to kinematic redundancy and the complexity of existing simulation environments like MuJoCo or ROS-Gazebo. This paper presents ArmReach6DOFEnv, a lightweight, open-source simulation framework built on PyBullet for rapid Reinforcement Learning (RL) prototyping on 6-DOF robotic arms. Using a Universal Robot Description Format (URDF) model, the environment supports a … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 11 Feb 2026 · 3,071 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Customer Predictive Model for Investment Using Ensemble Learning TechniqueThongchai Kaewkiriya, Kittipol WisaengMany new investors that want to purchase a fund might be disappointed with the return-on-investment value. This problem occurs because they do not know important factors that could affect the market value. Plus, some assets might not be suitable for the investor's investment style. To reduce the mentioned problems, many asset management companies research the systems that could find a … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,472 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Brain Tumor Diagnosis using Fused Layer AcceleratorMitrabinda Khuntia, Prabhat Kumar Sahu, Swagatika DeviDeep Convolutional Neural Networks (DCNNs) are an emerging field in biomedical processing. Tumor classification is a key stage in the pathology analysis process, and deep learning algorithms for brain tumor categorization have recently shown promising results. However, these approaches often require more storage and more expensive training procedures to input a large number of training variables. To address this issue, … …Journal of Computer Science, Vol. 19, Issue 2 · 19 Jan 2023 · 5,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Approach to Develop, Assess and Optimize Energy Consumption Models for Air-Cooled Chillers using Machine Learning AlgorithmsMostafa Tahmasebi, Nabil NassifThe building sector accounts for more than 70% of the total electricity use. Chillers consume more than 50% of electrical energy during seasonal periods of building use. With the growth of the building sector and climate change, it's essential to develop energy-efficient HVAC systems that optimize the ever-increasing energy demand. This study aims to develop an energy consumption prediction model … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 3 · 8 Nov 2022 · 5,516 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 accessesView PDFCite
Review ArticleOpen accessIn the abstractSurvey on Applications of Electronic NoseS. Keerthana, B. SanthiFood plays a vital role in our daily life. Providing good quality food to consumers is essential. Food quality can be accessed using the Electronic nose. Electronic nose (E-nose) is an instrument for odor analysis. E-nose mimics the human olfaction system. It is widely used in predicting the quality of foodstuffs and detecting the contamination in foods. E-nose can also … …Journal of Computer Science, Vol. 16, Issue 3 · 15 Mar 2020 · 8,173 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Deep Learning Libraries: TensorFlow and PyTorchFelipe Florencio, Thiago Valenç, Edward David Moreno, Methanias Colaço JuniorThrough the increase in deep learning study and use, in the last years there was a development of specific libraries for Deep Neural Network (DNN). Each one of these libraries has different performance results and applies different techniques to optimize the implementation of algorithms. Therefore, even though implementing the same algorithm and using different libraries, the performance of their executions … …Journal of Computer Science, Vol. 15, Issue 6 · 11 Apr 2019 · 10,293 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Collaborative Prediction of Presence of Arrhythmia in Human Heart with Electrocardiogram Data using Machine Learning Algorithms with AnalyticsSelvaraj Rajalakshmi, Kuthadi Venu MadhavHuman heart is the major organ of human being which could fail the other systems in the body at the same time. Hence predicting heart disease is one of the challenging researches that requires meticulous analysis of heart rhythms properly. The irregular heart rhythms or beat is referred to as the Arrhythmia where heart rhythms with low or high rates … …Journal of Computer Science, Vol. 15, Issue 2 · 22 Feb 2019 · 7,508 accessesView PDFCite