Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

73 results for “Learning Data type”

Set a search alert
Research ArticleOpen accessIn the abstractApplication of Data Enhancement Method Based on Generative Adversarial Networks for Soybean Leaf Disease IdentificationXiao Yu, Cong Chen, Qi Gong, Lina LuSoybean leaf disease data collection is an expensive and time-consuming task. Convolutional neural network training requires a large amount of data, but traditional data enhancement methods (such as rotation, flipping, translation) are restricted by fixed rules and cannot generate images with diversity and variability. Aiming at the problem of the lack of soybean leaf disease data set, this study proposes … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 4 · 26 Nov 2022 · 5,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Synthetic Oversampling Algorithm for Handling Class Imbalance in Multi-Class Data Stream ClassificationPriya S., Annie UthraConcept drift and class imbalanced data are major challenging processes involved in modern streaming data classification. Particularly, when integrated with difficult factors like the existence of noise, overlapping class distribution, concept drift, and data imbalance can considerably affect the classifier results. In addition, various challenges affect the performance of the existing oversampling schemes such as SMOTE and its derivatives. Regardless … …Journal of Computer Science, Vol. 18, Issue 7 · 26 Jul 2022 · 5,809 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Anomaly Detection Approach for Nifty Stocks using Machine Learning for Construction of Efficient Portfolio to Reduce Losses and Protect GainsVirrat Devaser, Priyanka ChawlaMachine Learning is the most essential and widely utilized methodological approach these days for performing, organizing, and analyzing data using a variety of approaches to produce correct and efficient results. Machine learning methodologies are also applicable to stock markets, which have grown multi-fold in recent years, and with the amount of money involved, the possibility of manipulation is always present … …Journal of Computer Science, Vol. 18, Issue 5 · 6 Jun 2022 · 6,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis for Reviewing Tourist Destinations in Saudi Arabia using Apache Spark and Machine Learning AlgorithmsWala Awadh Alasmari, Hoda Ahmed AbdelhafezThe appearance of big data has created new challenges for data analysis teams especially dealing with unstructured data in text form. Many applications increasingly include a large amount of this type of data. Example of such data is data collected from Twitter. Adequate use of Machine Learning (ML), big data tools and social media platforms can solve several problems. The … …Journal of Computer Science, Vol. 18, Issue 3 · 7 Apr 2022 · 7,241 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Model Predictive Control System Design and Implementation for Unmanned Ground VehiclesSai Charan Dekkata, Sun Yi, MA Muktadir et al.Autonomous ground robots autonomously are being used inthe places where it is very hazardous for human beings to reach and operate,such as nuclear power plants and chemical industries. The aim of the researchpresented here is to develop a control system that enables such ground robotsnavigate autonomously with various sensors as the depth camera, 2D scanninglaser, 3D Lidar, GPS, and IMU. … …Journal of Mechatronics and Robotics, Vol. 6, Issue 1 · 27 Oct 2022 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Non-Small Cell Lung Cancer Based on Gene Expression in Cases of Smokers and Non-Smokers using Ensemble Methods with Statistical Based Feature SelectionFhira Nhita, Isman KurniawanLung cancer is one of the leading causes of death globally. One of the main risk factors for lung can ceris smoking, which causes more than 90% of lung cancer cases. There are two types of lung cancer, i.e., Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC), which the latter is the most common. One method that … …Journal of Computer Science, Vol. 18, Issue 10 · 30 Sep 2022 · 6,093 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating Higher-Order Thinking Skills, Cognitive Load Theory, and Metacognition in Algebraic Problem-SolvingGurudeo Anand TularamThis study synthesizes 30 years of research (1990–2020) on algebraic problem-solving, integrating Higher-Order Thinking Skills (HOTS), Cognitive Load Theory (CLT), and metacognitive strategies to enhance student outcomes. Utilizing a critical synthesis approach with data from student interviews, problem-solving observations, and longitudinal tracking, the analysis reveals consistent patterns across diverse educational contexts despite limitations and variable factors like teaching styles and … …Journal of Social Sciences, Vol. 22, Issue 1 · 21 Apr 2026 · 2,016 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting the Remaining Lifetime of Distribution Transformers using Machine LearningNtiminity Abontakoyah Enoch, Puguo Gbene George, Justice AningDistribution Transformer is a crucial element in deciding the power flow in large power systems. Their better performance implies high power system efficiency and enhanced power transfer capability. However, various Distribution Transformer failures in the recent past lead to power supply disturbance and have acquired much attention from the electrical intellectuals. It is of considerable significance to accurately get the … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 1 Jan 2021 · 6,644 accessesView PDFCite