Zobrazeno 1 - 10
of 249
pro vyhledávání: '"Hammer, Hugo Lewi"'
Autor:
Sheshkal, Sajad Amouei, Gundersen, Morten, Riegler, Michael Alexander, Utheim, Øygunn Aass, Gundersen, Kjell Gunnar, Hammer, Hugo Lewi
Dry eye disease is a common disorder of the ocular surface, leading patients to seek eye care. Clinical signs and symptoms are currently used to diagnose dry eye disease. Metabolomics, a method for analyzing biological systems, has been found helpful
Externí odkaz:
http://arxiv.org/abs/2406.14068
Autor:
Thambawita, Vajira, Jha, Debesh, Hammer, Hugo Lewi, Johansen, Håvard D., Johansen, Dag, Halvorsen, Pål, Riegler, Michael A.
Precise and efficient automated identification of Gastrointestinal (GI) tract diseases can help doctors treat more patients and improve the rate of disease detection and identification. Currently, automatic analysis of diseases in the GI tract is a h
Externí odkaz:
http://arxiv.org/abs/2005.03912
The concept of depth represents methods to measure how deep an arbitrary point is positioned in a dataset and can be seen as the opposite of outlyingness. It has proved very useful and a wide range of methods have been developed based on the concept.
Externí odkaz:
http://arxiv.org/abs/2001.02393
Autor:
Heiney, Kristine, Valderhaug, Vibeke Devold, Sandvig, Ioanna, Sandvig, Axel, Tufte, Gunnar, Hammer, Hugo Lewi, Nichele, Stefano
Novel computing hardwares are necessary to keep up with today's increasing demand for data storage and processing power. In this research project, we turn to the brain for inspiration to develop novel computing substrates that are self-learning, scal
Externí odkaz:
http://arxiv.org/abs/1907.02351
Estimation of quantiles is one of the most fundamental real-time analysis tasks. Most real-time data streams vary dynamically with time and incremental quantile estimators document state-of-the art performance to track quantiles of such data streams.
Externí odkaz:
http://arxiv.org/abs/1902.05428
Autor:
Hammer, Hugo Lewi
Forecasting of future snow depths is useful for many applications like road safety, winter sport activities, avalanche risk assessment and hydrology. Motivated by the lack of statistical forecasts models for snow depth, in this paper we present a set
Externí odkaz:
http://arxiv.org/abs/1901.04695
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 track quantiles of data strea
Externí odkaz:
http://arxiv.org/abs/1901.04681
Autor:
Hammer, Hugo Lewi, Yazidi, Anis
Many real-life dynamical systems change abruptly followed by almost stationary periods. In this paper, we consider streams of data with such abrupt behavior and investigate the problem of tracking their statistical properties in an online manner. We
Externí odkaz:
http://arxiv.org/abs/1901.04678
Publikováno v:
Sheshkal SA, Riegler M, Hammer HL: ML-Peaks: Chip-seq peak detection pipeline using machine learning techniques. In: Placidi, González AR, Sicilia R, Spiliopoulou M, Almeida JR, Andrades. Proceedings of the 2023 36th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS), 2023. IEEE conference proceedings
Externí odkaz:
https://hdl.handle.net/10037/31697
Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure
Autor:
Storås, Andrea, Riegler, Michael Alexander, Haugen, Trine B., Thambawita, Vajira L B, Hicks, Steven Alexander, Hammer, Hugo Lewi, Kakulavarapu, Radhika, Halvorsen, Pål, Stensen, Mette Haug
Externí odkaz:
https://hdl.handle.net/11250/3093350