Now showing items 21-40 of 63

    • Dyadic Aggregated Autoregressive Model (DASAR) for Automatic Modulation Classification 

      Pinto-Orellana, Marco Antonio; Hammer, Hugo Lewi (IEEE Access;Volume 8, Journal article; Peer reviewed, 2020-08-27)
      In this article, we presented a novel spectral estimation method, the dyadic aggregated autoregressive model (DASAR), that characterizes the spectrum dynamics of a modulated signal. DASAR enhances automatic modulation ...
    • Efficient Tracking of Statistical Properties of Data Streams with Rapid Changes 

      Hammer, Hugo Lewi; Yazidi, Anis (The 26th Mediterranean Conference on Control and Automation;, Chapter; Chapter; Peer reviewed, 2018-08-23)
      Many real-life dynamical systems change rapidly followed by almost stationary periods. In this paper, we consider streams of data with such rapidly changing behavior and investigate the problem of tracking their statistical ...
    • Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Abolpour Mofrad, Samaneh; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Vol. 33, No. 2, Journal article; Peer reviewed, 2021-02-01)
      Formation of stimulus equivalence classes has been recently modeled through equivalence projective simulation (EPS), a modified version of a projective simulation (PS) learning agent. PS is endowed with an episodic memory ...
    • Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Volume 32, No. 5, Journal article; Peer reviewed, 2020-04-14)
      Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence ...
    • Game-Theoretic Learning for Sensor Reliability Evaluation Without Knowledge of the Ground Truth 

      Yazidi, Anis; Hammer, Hugo Lewi; Samouylov, Konstantin; Herrera-Viedma, Enrique (IEEE Transactions on Cybernetics;Date of Publication 06 January 2020, Journal article; Peer reviewed, 2020)
      Sensor fusion has attracted a lot of research attention during the few last years. Recently, a new research direction has emerged dealing with sensor fusion without knowledge of the ground truth. In this article, we present ...
    • GANEx: A complete pipeline of training, inference and benchmarking GAN experiments 

      Thambawita, Vajira; Hammer, Hugo Lewi; Riegler, Michael Alexander; Halvorsen, Pål (International Workshop on Content-Based Multimedia Indexing, CBMI;, Chapter; Conference object; Peer reviewed, 2019-10-21)
      Deep learning (DL) is one of the standard methods in the field of multimedia research to perform data classification, detection, segmentation and generation. Within DL, generative adversarial networks (GANs) represents a ...
    • Hvorfor trenger vi statistikk? 

      Brurberg, Kjetil Gundro; Hammer, Hugo Lewi (Sykepleien Forskning;8 (1), Journal article, 2013)
    • 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 ...
    • 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 ...