Blar i ODA Open Digital Archive på emneord "Machine learning"

Viser treff 21-40 av 50

    • Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review 

      Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (Information Fusion;Volume 59, July 2020, Peer reviewed; Journal article, 2020-01-31)
      In recent years, the rapid advances in machine learning (ML) and information fusion has made it possible to endow machines/computers with the ability of emotion understanding, recognition, and analysis. Emotion recognition ...

    • Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations 

      Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (RACS: Research in Applied Computation Symposium; RACS '20: International Conference on Research in Adaptive and Convergent Systems, Chapter; Peer reviewed; Conference proceeding, 2020-10)
      Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ...

    • Explaining deep neural networks for knowledge discovery in electrocardiogram analysis 

      Hicks, Steven; Isaksen, Jonas L; Thambawita, Vajira L B; Ghouse, Jonas; Ahlberg, Gustav; Linneberg, Allan; Grarup, Niels; Strumke, Inga; Ellervik, Christina; Olesen, Morten Salling; Hansen, Torben; Graff, Claus; Holstein-Rathlou, Niels-Henrik; Halvorsen, Pål; Maleckar, Mary Margot Catherine; Riegler, Michael; Kanters, Jørgen K (Scientific Reports;11, Article number: 10949 (2021), Peer reviewed; Journal article, 2021-05-26)
      Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any ...

    • Facial emotion recognition using deep learning 

      Kirkvik, Emilia Basioli (ACIT;2022, Master thesis, 2022)
      Rapid advancements in Machine Learning (ML) have made it possible to equip computers with the ability to analyze, recognize and understand emotions. Facial Emotion Recognition (FER) is a technology that analyzes facial ...

    • File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments 

      Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Riegler, Michael Alexander; Halvorsen, Pål; Johansen, Dag (Information;Volume 12, Issue 10, Peer reviewed; Journal article, 2021-10-18)
      In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform ...

    • Fog computing for sustainable smart cities in the IoT era: Caching techniques and enabling technologies - an overview 

      Zahmatkesh, Hadi; Al-Turjman, Fadi (Sustainable Cities and Society;Volume 59, August 2020, 102139, Journal article; Peer reviewed, 2020-04-29)
      In recent decade, the number of devices involved with the Internet of Things (IoT) phenomena has increased dramatically. Parallel to this, fog computing paradigm has been introduced in order to support the computational ...

    • Forecasting Economic Downturns in the Scandinavian Countries using The Yield Curve : Exploring statistical relationships and out-of-sample performance using traditional binary response models, and support vector machine models from the field of machine learning 

      Andersen, Sondre (Master thesis, 2020)
      Economic downturns (in this thesis defined as recessions and negative output gaps) are costly and it is in the interest of both the Government and private agents to precisely predict them, either for the government to ...

    • General TCP state inference model from passive measurements using machine learning techniques 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Kure, Øivind (IEEE Access;VOLUME 6, 2018, Journal article; Peer reviewed, 2018-05-04)
      Many applications in the Internet use the reliable end-to-end Transmission Control Protocol (TCP) as a transport protocol due to practical considerations. There are many different TCP variants widely in use, and each ...

    • HYPERAKTIV: An Activity Dataset from Patients with Attention-Deficit/Hyperactivity Disorder (ADHD) 

      Hicks, Steven; Stautland, Andrea; Fasmer, Ole Bernt; Førland, Wenche; Hammer, Hugo Lewi; Halvorsen, Pål; Mjeldheim, Kristin; Ødegaard, Ketil Joachim; Osnes, Berge; Syrstad, Vigdis Elin Giæver; Riegler, Michael; Jakobsen, Petter (MMSys: ACM Multimedia Systems;MMSys '21: Proceedings of the 12th ACM Multimedia Systems Conference, Conference object, 2021-09-22)
      Machine learning research within healthcare frequently lacks the public data needed to be fully reproducible and comparable. Datasets are often restricted due to privacy concerns and legal requirementsthat come with ...

    • Improving Cellular IoT Security with Identity Federation and Anomaly Detection 

      Santos, Bernardo; Dzogovic, Bruno; Feng, Boning; Jacot, Niels; Do, Thuan Van; Do, van Thanh (International Conference on Computers, Communications, and Systems (ICCCS);2020 5th International Conference on Computer and Communication Systems (ICCCS), Conference object, 2020-06-16)
      As we notice the increasing adoption of Cellular IoT solutions (smart-home, e-health, among others), there are still some security aspects that can be improved as these devices can suffer various types of attacks that can ...

    • Improving Phishing Detection with the Grey Wolf Optimizer 

      Naser Jaber, Aws; Fritsch, Lothar; Haugerud, Hårek (International Conference on Electronics, Information, and Communication (ICEIC);2022 International Conference on Electronics, Information, and Communication (ICEIC), Conference object, 2022-04-11)
      With the recent epidemic of COVID-19-themed scam and phishing, the efficient automated detection of such attacks is crucial. Although many anti-phishing solutions, such as lists and similarity and heuristic-based approaches ...

    • Intelligent Initiatives to Reduce CO2 Emissions in Construction 

      Farahzadi, Leila; Kioumarsi, Mahdi (Conference object, 2022-11-24)
      Global warming is one of the most important environmental issues that threatens the living on this globe so far. Carbon dioxide (CO2) emission from the construction industry is one of the major sources of emissions that ...

    • A Learning Automaton-based Scheme for Scheduling Domestic Shiftable Loads in Smart Grids 

      Thapa, Rajan; Lei, Jiao; Oommen, John; Yazidi, Anis (Journal article; Peer reviewed, 2017)
      In this paper, we consider the problem of scheduling shiftable loads, over multiple users, in smart electrical grids. We approach the problem, which is becoming increasingly pertinent in our present energy-thirsty society, ...

    • Machine learning-based abnormality detection approach for vacuum pump assembly line 

      Garg, Paras; Patil, Amitkumar; Soni, Gunjan; Keprate, Arvind; Arora, Seemant (Reliability: Theory & Applications;Special Issue No 2(64), Volume 16, November 2021, Peer reviewed; Journal article, 2021-11-04)
      The fundamental basis of Industry 4.0 is to make the manufacturing sector more productive and autonomous. In the manufacturing sector, practitioners always long for product quality improvement, reducing reworking costs, ...

    • A Machine Learning-based Tool for Passive OS Fingerprinting with TCP Variant as a Novel Feature 

      Hagos, Desta Haileselassie; Yazidi, Anis; Kure, Øivind; Engelstad, Paal (IEEE Internet of Things Journal;Volume: 8, Issue: 5, Peer reviewed; Journal article, 2020-09-15)
      With the emergence of Internet of Things (IoT), securing and managing large, complex enterprise network infrastructure requires capturing and analyzing network traffic traces in real-time. An accurate passive Operating ...

    • MachinelLearning to classify and recommend physical activity based on wearable technology 

      Shrestha, Dipak (MAUU;2020, Master thesis, 2020)
      Different wearable technology has been used to measure the physical activities of people with movement disorder through activity classification as well as recommending suitable physical activity level. A physical activity ...

    • Manifold feature fusion with dynamical feature selection for cross-subject emotion recognition 

      Hua, Yue; Zhong, Xiaolong; Zhang, Bingxue; Yin, Zhong; Zhang, Jianhua (Brain Sciences;Volume 11 / Issue 11, Peer reviewed; Journal article, 2021-10-23)
      Affective computing systems can decode cortical activities to facilitate emotional human– computer interaction. However, personalities exist in neurophysiological responses among different users of the brain–computer ...

    • Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks 

      Mello, Gustavo; Pontes-Filho, Sidney; Sandvig, Ioanna; Valderhaug, Vibeke Devold; Zouganeli, Evi; Huse Ramstad, Ola; Sandvig, Axel; Nichele, Stefano (IEEE Symposium Series on Computational Intelligence (SSCI);, Chapter; Peer reviewed, 2020-02-20)
      In the brain, the structure of a network of neurons defines how these neurons implement the computations that underlie the mind and the behavior of animals and humans. Provided that we can describe the network of neurons ...

    • Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis 

      Maglanoc, Luigi Angelo; Kaufmann, Tobias; Jonassen, Rune; Hilland, Eva; Beck, Dani; Landrø, Nils Inge; Westlye, Lars Tjelta (Human Brain Mapping;Volume 41, Issue 1, January 2020, Journal article; Peer reviewed, 2019-09-09)
      Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be ...

    • A neural network model and framework for an automatic evaluation of image descriptions based on NCAM image accessibility guidelines 

      Shrestha, Raju (Chapter; Peer reviewed, 2021)
      Millions of people who are either blind or visually impaired have difficulty understanding the content in an image. To address the problem textual image descriptions or captions are provided separately or as alternative ...