Blar i Institutt for datateknologi og informatikk på tidsskrift "IEEE Access"
Viser treff 41-60 av 69
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Machine Learning in Financial Market Surveillance: A Survey
(Peer reviewed; Journal article, 2021)The use of machine learning for anomaly detection is a well-studied topic within various application domains. However, the detection problem for market surveillance remains challenging due to the lack of labeled data and ... -
maplib: Interactive, Literal RDF Model Mapping for Industry
(Peer reviewed; Journal article, 2023)Knowledge graphs are important for industrial digitalization. Industrial knowledge graphs are often mapped from multiple existing large data sources, and creating a mapping requires the time of scarce subject matter experts ... -
A Model-Driven Approach for the Management and Enforcement of Coding Conventions
(Journal article; Peer reviewed, 2023) -
MSS-WISN: Multiscale Multistaining WBCs Instance Segmentation Network
(Journal article; Peer reviewed, 2022) -
Multichannel Residual Cues for Fine-Grained Classification in Wireless Capsule Endoscopy
(Peer reviewed; Journal article, 2022)Early diagnosis of gastrointestinal pathologies leads to timely medical intervention and prevents disease development. Wireless Capsule Endoscopy (WCE) is used as a non-invasive alternative for gastrointestinal examination. ... -
A Novel Architectural Framework on IoT Ecosystem, Security Aspects and Mechanisms: A Comprehensive Survey
(Peer reviewed; Journal article, 2022)For the past few years, the Internet of Things (IoT) technology continues to not only gain popularity and importance, but also witnesses the true realization of everything being smart. With the advent of the concept of ... -
A Novel Mean-Shift Algorithm for Data Clustering
(Peer reviewed; Journal article, 2022)We propose a novel Mean-Shift method for data clustering, called Robust Mean-Shift (RMS). A new update equation for point iterates is proposed, mixing the ones of the standard Mean-Shift (MS) and the Blurring Mean-Shift ... -
Online Machine Learning for 1-Day-Ahead Prediction of Indoor Photovoltaic Energy
(Peer reviewed; Journal article, 2023)We explore the potential for predicting indoor photovoltaic energy on a forecasting horizon of up to 24 hours. The objective is to enable energy management approaches that exploit harvesting opportunities more strategically, ... -
Ontology-Based Fault Tree Analysis Algorithms in a Fuzzy Environment for Autonomous Ships
(Peer reviewed; Journal article, 2021)This study deals with fault tree analysis algorithms based on an ontology-based approach in a fuzzy environment. We extend fuzzy fault tree analysis by embedding ontology-based fault tree structures. The ontology-based ... -
Precious Metal Price Prediction based on Deep Regularization Self-Attention Regression
(Journal article; Peer reviewed, 2020)It is non-trivial to predict the prices of precious metals since a number of factors can affect the fluctuations of precious metal prices. Either parametric models or machine learning models cannot accurately forecast the ... -
Preventing Over-Enhancement Using Modified ICSO Algorithm
(Peer reviewed; Journal article, 2023)This paper proposes an Image Contrast Enhancement (ICE) method based on using an Improved Chicken Swarm Optimization (ICSO) algorithm to enhance images while at the same time preventing over-enhancement. In the optimization ... -
A Real-Time CNN-Based Lightweight Mobile Masked Face Recognition System
(Journal article; Peer reviewed, 2022) -
A Review on Traditional Machine Learning and Deep Learning Models for WBCs Classification in Blood Smear Images
(Peer reviewed; Journal article, 2021)In computer vision, traditional machine learning (TML) and deep learning (DL) methods have significantly contributed to the advancements of medical image analysis (MIA) by enhancing prediction accuracy, leading to appropriate ... -
A Review on Traditional Machine Learning and Deep Learning Models for WBCs Classification in Blood Smear Images
(Peer reviewed; Journal article, 2020)In computer vision, traditional machine learning (TML) and deep learning (DL) methods have significantly contributed to the advancements of medical image analysis (MIA) by enhancing prediction accuracy, leading to appropriate ... -
Semi-supervised Network for Detection of COVID-19 in Chest CT Scans
(Peer reviewed; Journal article, 2020)Deep Learning-based chest Computed Tomography (CT) analysis has been proven to be effective and efficient for COVID-19 diagnosis. Existing deep learning approaches heavily rely on large labeled data sets, which are difficult ... -
Sentiment Analysis of Chinese Microblog Based on Stacked Bidirectional LSTM
(Journal article; Peer reviewed, 2019)Sentiment analysis on Chinese microblogs has received extensive attention recently. Most previous studies focus on identifying sentiment orientation by encoding as many wordproperties as possible while they fail to consider ... -
Soaring Energy Prices: Understanding Public Engagement on Twitter Using Sentiment Analysis and Topic Modeling With Transformers
(Peer reviewed; Journal article, 2023)Energy prices have gone up gradually since last year, but a drastic hike has been observed recently in the past couple of months, affecting people’s thrift. This, coupled with the load shedding and energy shortages in some ... -
Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
(Peer reviewed; Journal article, 2021)The gradual prevalence of Internet of Things (IoT) and wireless communication technologies has enabled the wide adoption of various smart devices (e.g., smart watches) in provisioning the healthcare services to massive ... -
A Systematic Literature Review on Text Generation Using Deep Neural Network Models
(Peer reviewed; Journal article, 2022)In recent years, significant progress has been made in text generation. The latest text generation models are revolutionizing the domain by generating human-like text. It has gained wide popularity recently in many domains ... -
A Systematic Mapping Review on MOOC Recommender Systems
(Journal article; Peer reviewed, 2021)