Konu "Machine learning" için listeleme
Toplam kayıt 28, listelenen: 1-20
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Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values Under Symmetric and Asymmetric Faults
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2021)Modern power systems require increased connectivity to implement novel coordination and control schemes. Wide-spread use of information technology in smartgrid domain is an outcome of this need. IEC 61850-based communication ... -
Automated processing and classification of medical thermal images
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)The aim of this dissertation is to develop computer aided methods for processing and evaluating medical infrared thermal images. Throughout this study three problems were evaluated. The first problem was to automatically ... -
Automated quantification of immunomagnetic beads and leukemia cells from optical microscope images
(ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2019)Quantification of tumor cells is crucial for early detection and monitoring the progress of cancer. Several methods have been developed for detecting tumor cells. However, automated quantification of cells in the presence ... -
Building a challenging medical dataset for comparative evaluation of classifier capabilities
(ELSEVIER, 2024)Since the 2000s, digitalization has been a crucial transformation in our lives. Nevertheless, digitalization brings a bulk of unstructured textual data to be processed, including articles, clinical records, web pages, and ... -
Can artificial intelligence and green finance affect economic cycles?
(ELSEVIER, 2024)The COVID-19 recession and the Ukraine-Russia War (URW) crisis have added a new layer of complexity to global economic cycles, necessitating the evolution of economic systems and proactive responses to emerging economic ... -
CCPred: Global and population-specific colorectal cancer prediction and metagenomic biomarker identification at different molecular levels using machine learning techniques
(ELSEVIER, 2024)Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and ... -
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ... -
A comprehensive experimental and modeling study of the strain rate- and temperature-dependent deformation behavior of bio-degradable Mg-CeO2 nanocomposites
(ELSEVIER, 2024)A comprehensive study was undertaken on the temperature-dependent and strain rate-sensitive deformation behavior of near-dense low-volume fraction magnesium-cerium dioxide (Mg-CeO2 ) nanocomposites synthesized by powder ... -
CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images
(ELSEVIER, 2023)COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have utilised Chest X-ray ... -
Deep Learning Based Employee Attrition Prediction
(SPRINGER LINK, 2023)Employee attrition is a critical issue for the business sectors as leaving employees cause various types of difficulties for the company. Some studies exist on examining the reasons for this phenomenon and predicting it ... -
Edge AI: A Taxonomy, Systematic Review and Future Directions
(SPRINGER, 2024)Edge Artificial Intelligence (AI) incorporates a network of interconnected systems and devices that receive, cache, process, and analyse data in close communication with the location where the data is captured with AI ... -
EdgeAISim: A toolkit for simulation and modelling of AI models in edge computing environments
(ELSEVIER, 2024)To meet next-generation Internet of Things (IoT) application demands, edge computing moves processing power and storage closer to the network edge to minimize latency and bandwidth utilization. Edge computing is becoming ... -
An efficient network intrusion detection approach based on logistic regression model and parallel artificial bee colony algorithm
(ELSEVIER, 2024)In recent years, the widespread use of the Internet has created many issues, especially in the area of cybersecurity. It is critical to detect intrusions in network traffic, and researchers have developed network intrusion ... -
An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms
(SPRINGER, 2023)Among text-mining studies, one of the most studied topics is the text classifcation task applied in various domains, including medicine, social media, and academia. As a sub-problem in text classifcation, sentiment ... -
Ensemble feature selection and classification methods for machine learning-based coronary artery disease diagnosis
(ELSEVIER, 2023)Coronary artery disease (CAD) is a condition in which the heart is not fed sufficiently as a result of the accumulation of fatty matter. As reported by the World Health Organization, around 32% of the total deaths in the ... -
Lung cancer subtype differentiation from positron emission tomography images
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2020)Lung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation ... -
Machine and deep learning based analysis of tumors on FDG-PET images
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)Analysis of a tumor is essential in treatment planning and evaluation of treatment response. Positron Emission Tomography (PET) is a vital imaging device for clinical oncology in understanding the metabolic structure of ... -
Machine learning approaches for underwater sensor network parameter prediction
(ELSEVIER, 2023)Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low ... -
Microstructural, mechanical, tribological, and corrosion behavior of ultrafine bio-degradable Mg/CeO2 nanocomposites: Machine learning-based modeling and experiment
(ELSEVIER SCI LTD, 2023)The present study investigated the microstructural, mechanical, tribological, and corrosion behavior of near-dense and low-volume fraction magnesium-cerium dioxide (Mg/CeO2 ) (x = 0.5, 1, and 1.5 vol.%) nanocomposites ... -
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
(PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021)A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high ...
