Zobrazeno 1 - 10
of 341
pro vyhledávání: '"Ward Tomas"'
Motor imagery-based BCI systems have been promising and gaining popularity in rehabilitation and Activities of daily life(ADL). Despite this, the technology is still emerging and has not yet been outside the laboratory constraints. Channel reduction
Externí odkaz:
http://arxiv.org/abs/2406.14179
Battery Electric Vehicles (BEVs) are increasingly significant in modern cities due to their potential to reduce air pollution. Precise and real-time estimation of energy consumption for them is imperative for effective itinerary planning and optimizi
Externí odkaz:
http://arxiv.org/abs/2312.07371
Autor:
Totev, Andrey, Ward, Tomas
Offline handwriting recognition (HWR) has improved significantly with the advent of deep learning architectures in recent years. Nevertheless, it remains a challenging problem and practical applications often rely on post-processing techniques for re
Externí odkaz:
http://arxiv.org/abs/2309.10158
Evaluating the quality of videos generated from text-to-video (T2V) models is important if they are to produce plausible outputs that convince a viewer of their authenticity. We examine some of the metrics used in this area and highlight their limita
Externí odkaz:
http://arxiv.org/abs/2309.08009
Autor:
Monacelli, Greta, Zhang, Lili, Schlee, Winfried, Langguth, Berthold, Ward, Tomás E., Murphy, Thomas B.
Recently the use of mobile technologies in Ecological Momentary Assessments (EMA) and Interventions (EMI) has made it easier to collect data suitable for intra-individual variability studies in the medical field. Nevertheless, especially when self-re
Externí odkaz:
http://arxiv.org/abs/2207.12331
Autor:
Bakerly, Nawar D., Balasundaram, Kumaran, Ball, Megan, Barahona, Mauricio, Casson, Alexander, Clarke, Jonathan, Cook, Karen, Cooper, Rowena, Curcin, Vasa, Darbyshire, Julie, Davies, Helen E., Dawes, Helen, de Lusignan, Simon, Delaney, Brendan, Echevarria, Carlos, Elkin, Sarah, Espinosa Gonzalez, Ana Belen, Evans, Rachael, Evans, Sophie, Falope, Zacchaeus, Glampson, Ben, Goodwin, Madeline, Greenhalgh, Trish, Greenwood, Darren C., Halpin, Stephen, Harris, Juliet, Hinton, Will, Horton, Mike, Jones, Samantha, Kwon, Joseph, Lee, Cassie, Lovett, Ashliegh, Mansoubi, Mae, Masey, Victoria, Master, Harsha, Mayer, Erik, Meza-Torres, Bernardo, Milne, Ruairidh, Mir, Ghazala, Morris, Jacqui, Mosley, Adam, Mullard, Jordan, O'Connor, Daryl, O'Connor, Rory, Osborne, Thomas, Parkin, Amy, Petrou, Stavros, Pick, Anton, Prociuk, Denys, Rayner, Clare, Rebane, Amy, Rogers, Natalie, Scott, Janet T., Sivan, Manoj, Smith, Adam B., Smith, Nikki, Tucker, Emma, Tucker-Bell, Ian, Williams, Paul, Winch, Darren, Wood, Conor, Mansoubi, Maedeh, Bhatia, Aishwarya, Collett, Johnny, Dawes, Joanna, Ezekiel, Leisle, Leveridge, Phaedra, Muhlhausen, Willie, Read, Flo, Tucker–Bell, Ian, Vashisht, Himanshu, Ward, Tomás, O'Connor, Daryl B.
Publikováno v:
In The Lancet Regional Health - Europe November 2024 46
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:
http://arxiv.org/abs/2201.07649
Continuous medical time series data such as ECG is one of the most complex time series due to its dynamic and high dimensional characteristics. In addition, due to its sensitive nature, privacy concerns and legal restrictions, it is often even comple
Externí odkaz:
http://arxiv.org/abs/2111.00314
Bitcoin is firmly becoming a mainstream asset in our global society. Its highly volatile nature has traders and speculators flooding into the market to take advantage of its significant price swings in the hope of making money. This work brings an al
Externí odkaz:
http://arxiv.org/abs/2110.14936
Sensitive medical data is often subject to strict usage constraints. In this paper, we trained a generative adversarial network (GAN) on real-world electronic health records (EHR). It was then used to create a data-set of "fake" patients through synt
Externí odkaz:
http://arxiv.org/abs/2109.02543