Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Eoin Brophy"'
Publikováno v:
IEEE Access, Vol 10, Pp 54891-54898 (2022)
Heart disease is the leading cause of mortality worldwide, and it is of utmost importance that clinicians and researchers understand the dynamics of the heart. As an electrical measure of the heart’s activity, the electrocardiogram, or ECG, is the
Externí odkaz:
https://doaj.org/article/5277727d86804ea3ae4521d64b88b084
Publikováno v:
IEEE Access, Vol 9, Pp 158936-158945 (2021)
Access to medical data is highly regulated due to its sensitive nature, which can constrain communities’ ability to utilize these data for research or clinical purposes. Common de-identification techniques to enable the sharing of data may not prov
Externí odkaz:
https://doaj.org/article/8f89ee4b8466413ea9b800b9c824e0be
Publikováno v:
Frontiers in Neuroergonomics, Vol 2 (2022)
As a measure of the brain's electrical activity, electroencephalography (EEG) is the primary signal of interest for brain-computer-interfaces (BCI). BCIs offer a communication pathway between a brain and an external device, translating thought into a
Externí odkaz:
https://doaj.org/article/da7c9ba1b0364b1985b0283d8163db89
Publikováno v:
Sensors, Vol 21, Iss 18, p 6311 (2021)
Ischemic heart disease is the highest cause of mortality globally each year. This puts a massive strain not only on the lives of those affected, but also on the public healthcare systems. To understand the dynamics of the healthy and unhealthy heart,
Externí odkaz:
https://doaj.org/article/4759249cb6934c99b7f261cc33ad7d53
Publikováno v:
Brophy, Eoin, She, Qi, Wang, Zhengwei ORCID: 0000-0001-7706-553X and Ward, Tomás E. ORCID: 0000-0002-6173-6607 (2023) Generative adversarial networks in time series: a systematic literature review. ACM Computing Surveys, 55 (10). ISSN 0360-0300
Generative adversarial network (GAN) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image and video manipulation, especially generation, making significant advance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59e7197490902457bd44cd95a3351d72
http://doras.dcu.ie/28088/
http://doras.dcu.ie/28088/
Autor:
Qihan Yang, Somesh Kumar, Qiaoyong Zhong, Fan Feng, Liang Ma, Qi She, Siew-Kei Lam, Gabriele Graffieti, German Ignacio Parisi, Yangsheng Xu, Baoquan Chen, Tin Lun Lam, Eoin Brophy, Chuanlin Lan, Vidit Goel, Lin Yang, Qi Liu, Rosa H. M. Chan, Debdoot Sheet, Shiliang Pu, Di Xie, Lorenzo Pellegrini, Hyonyoung Han, Liguang Zhou, Vincenzo Lomonaco, Zhengwei Wang, Soonyong Song, Davide Maltoni, Heechul Bae, Jianwen Wu, Xinyue Hao, Tomas E. Ward, Duvindu Piyasena, Sathursan Kanagarajah, Meiqing Wu, Young-Sung Son
Publikováno v:
IEEE Robotics & Automation Magazine. 27:11-16
Humans have a remarkable ability to learn continuously from th e environment and inner experience. One of the grand goals of robots is to build an artificial "lifelong learning" agent that can shape a cultivated understanding of the world from the cu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26ea5e8210ef6c78f2ba2436e0e0d4c1
https://doi.org/10.1109/mra.2020.2987186
https://doi.org/10.1109/mra.2020.2987186
Network and system security are incredibly critical issues now. Due to the rapid proliferation of malware, traditional analysis methods struggle with enormous samples. In this paper, we propose four easy-to-extract and small-scale features, including
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca426a4501ee4ba023f747dd71ee8607
https://doi.org/10.36227/techrxiv.17259806.v1
https://doi.org/10.36227/techrxiv.17259806.v1
Publikováno v:
Brophy, Eoin, De Vos, Maarten ORCID: 0000-0002-3482-5145 , Boylan, Geraldine ORCID: 0000-0003-0920-5291 and Ward, Tomás E. ORCID: 0000-0002-6173-6607 (2021) Multivariate generative adversarial networks and their loss functions for synthesis of multichannel ECGs. IEEE Access, 9 . pp. 158936-158945. ISSN 2169-3536
IEEE Access, Vol 9, Pp 158936-158945 (2021)
IEEE Access, Vol 9, Pp 158936-158945 (2021)
Access to medical data is highly regulated due to its sensitive nature, which can constrain communities’ ability to utilize these data for research or clinical purposes. Common de-identification techniques to enable the sharing of data may not prov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97555788b584890e8799b5c3a2982def
http://doras.dcu.ie/27536/
http://doras.dcu.ie/27536/
Autor:
Eoin Brophy
Publikováno v:
CIKM
Access to medical data is highly regulated due to its sensitive nature, which can constrain communities' ability to utilise these data for research or clinical purposes. Common de-identification techniques to enable the sharing of data may not provid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80b25165f93ae178723058f923c5db9f
https://doi.org/10.1145/3340531.3418509
https://doi.org/10.1145/3340531.3418509
Publikováno v:
PerCom
When you call the RCNN function you can specify Cony Pooling params which will affect the outcome of your heart rate error. Your choice of cony -pooling f ilter(cv_k) and stride(cv_k) sizes will be dependent on seq_len that changes with you downsampl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efb0c3fc94e1d5ae92040f3a12b2106e
https://doi.org/10.1109/percom45495.2020.9127368
https://doi.org/10.1109/percom45495.2020.9127368