Blar i ODA Open Digital Archive på forfatter "Hammer, Hugo Lewi"

Viser treff 41-60 av 85

    • 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 ...

    • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy 

      Borgli, Hanna; Thambawita, Vajira; Smedsrud, Pia H; Hicks, Steven; Jha, Debesh; Eskeland, Sigrun Losada; Randel, Kristin Ranheim; Pogorelov, Konstantin; Lux, Mathias; Dang Nguyen, Duc Tien; Johansen, Dag; Griwodz, Carsten; Stensland, Håkon Kvale; Garcia-Ceja, Enrique; Schmidt, Peter T; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas (Scientific Data;7, Article number: 283 (2020), Journal article; Peer reviewed, 2020-08-28)
      Artifcial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually ...

    • Improving Classification of Tweets Using Linguistic Information from a Large External Corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Journal article; Peer reviewed, 2016)
      The bag of words representation of documents is often unsat- isfactory as it ignores relationships between important terms that do not co-occur literally. Improvements might be achieved by expanding the vocabulary with ...

    • Improving classification of tweets using word-word co-occurrence information from a large external corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Chapter; Peer reviewed; Chapter, 2016)
      Classifying tweets is an intrinsically hard task as tweets are short messages which makes traditional bags of words based approach ine cient. In fact, bags of words approaches ig- nores relationships between important ...

    • Incremental Quantiles Estimators for Tracking Multiple Quantiles 

      Hammer, Hugo Lewi; Yazidi, Anis (Journal article; Peer reviewed, 2017)
      In this paper, we investigate the problem of estimating multiple quantiles when samples are received online (data stream). We assume that we are dealing with a dynamical system, i.e. the distribution of the samples from ...

    • Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models 

      Tveitstøl, Thomas; Tveter, Mats; Pérez Teseyra, Ana Silvina; Hatlestad-Hall, Christoffer; Yazidi, Anis; Hammer, Hugo Lewi; Haraldsen, Ira Hebold (Peer reviewed; Journal article, 2023)
      Introduction: A challenge when applying an artificial intelligence (AI) deep learning (DL) approach to novel electroencephalography (EEG) data, is the DL architecture’s lack of adaptability to changing numbers of EEG ...

    • Joint tracking of multiple quantiles through conditional quantiles 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Information Sciences;Volume 563, July 2021, Peer reviewed; Journal article, 2021-03-05)
      The estimation of quantiles is one of the most fundamental data mining tasks. As most real-time data streams vary dynamically over time, there is a quest for adaptive quantile estimators. The most well-known type of adaptive ...

    • Kvasir-Capsule, a video capsule endoscopy dataset 

      Smedsrud, Pia H; Thambawita, Vajira L B; Hicks, Steven; Gjestang, Henrik; Olsen Nedrejord, Oda; Næss, Espen; Borgli, Hanna; Jha, Debesh; Berstad, Tor Jan; Eskeland, Sigrun Losada; Lux, Mathias; Espeland, Håvard; Petlund, Andreas; Dang Nguyen, Duc Tien; Garcia, Enrique; Johansen, Dag; Schmidt, Peter Thelin; Toth, Ervin; Hammer, Hugo Lewi; de Lange, Thomas; Riegler, Michael Alexander; Halvorsen, Pål (Scientific Data;8, Article number: 142 (2021), Peer reviewed; Journal article, 2021-05-27)
      Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work ...

    • Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction 

      Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Lasantha Bandara Thambawita, Vajira; Halvorsen, Pål; Hammer, Hugo Lewi; Haugen, Trine B.; Riegler, Michael Alexander (Scientific Reports;9, Article number: 16770 (2019), Journal article; Peer reviewed, 2019-10-24)
      Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human reproduction, clinical and biological data are ...

    • Microbial specialists in below-grade foundation walls in Scandinavia 

      Nunez, Maria; Hammer, Hugo Lewi (Indoor air;24(5), Journal article; Peer reviewed, 2014-02-17)
      Below-grade foundation walls are often exposed to excessive moisture by water infiltration, condensation, leakage, or lack of ventilation. Microbial growth in these structures depends largely on environmental factors, ...

    • Mitigating DDoS using weight-based geographical clustering 

      Kongshavn, Madeleine; Haugerud, Hårek; Yazidi, Anis; Maseng, Torleiv; Hammer, Hugo Lewi (Concurrency and Computation: Practice and Experience;Volume 32, Issue 11, e5679, Journal article; Peer reviewed, 2020-02-22)
      Distributed denial of service (DDoS) attacks have for the last two decades been among the greatest threats facing the internet infrastructure. Mitigating DDoS attacks is a particularly challenging task as an attacker tries ...

    • Multiplicative Update Methods for Incremental Quantile Estimation 

      Yazidi, Anis; Hammer, Hugo Lewi (IEEE Transactions on Cybernetics;VOL. 49, NO. 3, Journal article; Peer reviewed, 2019)
      We present a novel lightweight incremental quantile estimator which possesses far less complexity than the Tierney's estimator and its extensions. Notably, our algorithm relies only on tuning one single parameter which is ...

    • A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality 

      Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Cognitive Neurodynamics;, Journal article; Peer reviewed, 2020-06-11)
      Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ...

    • A new quantile tracking algorithm using a generalized exponentially weighted average of observations 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Applied Intelligence;Published online 10 November, 2018, Journal article; Journal article; Peer reviewed, 2018-11-10)
      The Exponentially Weighted Average (EWA) of observations is known to be state-of-art estimator for tracking expectations of dynamically varying data stream distributions. However, how to devise an EWA estimator to rather ...

    • A Novel Clustering Algorithm based on a Non-parametric "Anti-Bayesian" Paradigm 

      Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Lecture Notes in Computer Science;, Journal article; Peer reviewed, 2015-05-01)
      The problem of clustering, or unsupervised classification, has been solved by a myriad of techniques, all of which depend, either directly or implicitly, on the Bayesian principle of optimal classification. To be more ...

    • A Novel Incremental Quantile Estimator Using the Magnitude of the Observations 

      Hammer, Hugo Lewi; Yazidi, Anis (The 26th Mediterranean Conference on Control and Automation;, Chapter; Chapter; Peer reviewed, 2018-08-23)
      Incremental quantile estimators like the the deterministic multiplicative incremental quantile estimator by Yazidi and Hammer (2017) are simple and efficient algorithms to estimate and track quantiles when data are received ...

    • On solving the SPL problem using the concept of probability flux 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi (Applied intelligence;Volume 49, Issue 7, July 2019, Journal article; Peer reviewed, 2019-02-02)
      The Stochastic Point Location (SPL) problem [20] is a fundamental learning problem that has recently found a lot of research attention. SPL can be summarized as searching for an unknown point in an interval under faulty ...

    • On the Classification of Dynamical Data Streams Using Novel “Anti–Bayesian” Techniques 

      Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Journal article; Peer reviewed, 2018)
      The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, ...

    • On Using Novel "Anti-Bayesian" Techniques for the Classification of Dynamical Data Streams 

      Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Chapter; Peer reviewed, 2017)
      The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any ...

    • Parameter estimation in abruptly changing dynamic environments using stochastic learning weak estimator 

      Hammer, Hugo Lewi; Yazidi, Anis (Applied Intelligence;Volume 48, Issue 11, Journal article; Peer reviewed, 2018-05-25)
      Many real-life dynamical systems experience abrupt changes followed by almost stationary periods. In this paper, we consider streams of data exhibiting such abrupt behavior and investigate the problem of tracking their ...