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1
The manuscripts of the Middle English Lay Folks’ Mass Book in context
Smith, Jeremy J.. - : Sciendo, 2021
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2
The pragmatics of punctuation in Middle English documentary texts
Smith, Jeremy J.. - : John Benjamins Publishing Company, 2020
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3
Recuperating Older Scots in the early 18th century
Smith, Jeremy J.. - : John Benjamins Publishing Company, 2020
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4
Methodising Scots: the cases of Allan Ramsay and Thomas Ruddiman
Smith, Jeremy. - : University of South Carolina, 2020
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5
Godly vocabulary in Early Modern English religious debate
Smith, Jeremy J.. - : John Benjamins Publishing Company, 2020
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6
On scriptae: correlating spelling and script in late Middle English
Smith, Jeremy. - : Universidad de la Laguna, 2020
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7
Transforming Early English: the Reinvention of Early English and Older Scots
Smith, Jeremy J.. - : Cambridge University Press, 2020
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8
Charles d'Orleans and his finding of English
Smith, Jeremy J.. - : Boydell & Brewer, 2020
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9
Methodising Scots: the Cases of Allan Ramsay & Thomas Ruddiman
In: Studies in Scottish Literature (2020)
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10
'The Lay Folks' Mass Book' and Thomas Frederick Simmons: medievalism and the Tractarians
Jasper, David; Smith, Jeremy. - : Cambridge University Press, 2019
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11
Chaucer's linguistic invention
Smith, Jeremy J.. - : Cambridge University Press, 2019
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12
Chaucer and London English
Smith, Jeremy J.. - : Cambridge University Press, 2019
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13
The inventions of Sir Thomas Urquhart
Smith, Jeremy. - : Medieval Institute Publications, 2018
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14
The afterlives of Nicholas Love
Smith, Jeremy J.. - : Taylor & Francis, 2017
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15
From secreit script to public print: punctuation, news management and the condemnation of the Earl of Bothwell
Smith, Jeremy J.. - : University of California Press, 2017
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16
Multiscale Convolutional Neural Networks for Hand Detection
Abstract: Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs) in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN) model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.
URL: http://livrepository.liverpool.ac.uk/3006859/
http://livrepository.liverpool.ac.uk/3006859/1/Author_Tex.pdf
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17
The evolution of Old and Middle English texts: linguistic form and practices of literacy
Smith, Jeremy. - : Cambridge University Press, 2016
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18
Scots and English across the Union: linguistic connexions and contrasts
Smith, Jeremy. - : Association for Scottish Literary Studies, 2016
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19
Developments in English: expanding electronic evidence
Taavitsainen, Irma; Kytö, Merja; Claridge, Claudia. - : Cambridge University Press, 2015
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20
Religious discourse and the history of English
Kohnen, Thomas. - : Cambridge University Press, 2015
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