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Akademický článek

Challenges of Labelling Unknown Seabed Munition Dumpsites from Acoustic and Optical Surveys: A Case Study at Skagerrak

Autor: Oscar Bryan, Roy Edgar Hansen, Tom S. F. Haines, Narada Warakagoda, Alan Hunter

Publikováno v: Remote Sensing, Vol 14, Iss 11, p 2619 (2022)

The disposal of unexploded ordnance (UXOs) at sea is a global problem. The mapping and remediation of historic UXOs can be assisted by autonomous underwater vehicles (AUVs) carrying sensor payloads such as synthetic aperture sonar (SAS) and optical c

Externí odkaz: https://doaj.org/article/2d42ad5327fa44818283b6426ae2c400

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Synthetic cannabinoid receptor agonists are monoamine oxidase‐A selective inhibitors

Autor: Sarah A. Hindson, Rachael C. Andrews, Michael J. Danson, Marc W. van der Kamp, Amy E. Manley, Oliver B. Sutcliffe, Tom S. F. Haines, Tom P. Freeman, Jennifer Scott, Stephen M. Husbands, Ian S. Blagbrough, J. L. Ross Anderson, David R. Carbery, Christopher R. Pudney

Publikováno v: The FEBS Journal.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::69651668a6e2c61d655cceedf45ebe22
https://doi.org/10.1111/febs.16741

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Author response for 'Synthetic Cannabinoid Receptor Agonists are Monoamine Oxidase‐A Selective Inhibitors'

Autor: null Sarah A Hindson, null Rachael C Andrews, null Michael J Danson, null Marc W van der Kamp, null Amy E Manley, null Oliver B Sutcliffe, null Tom S F Haines, null Tom P Freeman, null Jennifer Scott, null Stephen M Husbands, null Ian S Blagbrough, null JL Ross Anderson, null David R Carbery, null Christopher R Pudney

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ec3150d3e81622ba4769c3da883a5143
https://doi.org/10.1111/febs.16741/v2/response1

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Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection

Autor: Rachael C. Andrews, Benedict May, Federico J. Hernández, Gyles E. Cozier, Piers A. Townsend, Oliver B. Sutcliffe, Tom S. F. Haines, Tom P. Freeman, Jennifer Scott, Stephen M. Husbands, Ian S. Blagbrough, Richard W. Bowman, Simon E. Lewis, Matthew N. Grayson, Rachel Crespo-Otero, David R. Carbery, Christopher R. Pudney

Publikováno v: Andrews, R, May, B, Hernández, F J, Townsend, P, Cozier, G, Sutcliffe, O B, Haines, T S F, Freeman, T, Scott, J, Husbands, S, Blagbrough, I, Bowman, R, Lewis, S, Grayson, M, Crespo-Otero, R, Carbery, D & Pudney, C 2023, ' Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; Toward Robust Point-of-Care Detection ', Analytical Chemistry, vol. 95, no. 2, pp. 703-713 . https://doi.org/10.1021/acs.analchem.2c02529

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfb29a0a735fdb72df53a08ddda7c2b1
https://pubmed.ncbi.nlm.nih.gov/36599091

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Automatic recognition of underwater munitions from multi-view sonar surveys using semi supervised machine learning: a simulation study

Autor: Oscar Bryan, Tom S. F. Haines, Alan Hunter, Roy Edgar Hansen, Narada Warakagoda

Publikováno v: Bryan, O, Hunter, A J, Haines, T S F, Hansen, R E & Warakagoda, N 2022, ' Automatic recognition of underwater munitions from multi-view sonar surveys using semi supervised machine learning: a simulation study ', Proceedings of Meetings on Acoustics, vol. 47, no. 1, 070018 . https://doi.org/10.1121/2.0001632

This paper presents a machine learning technique for using large unlabelled survey datasets to aid automatic classification. We have demonstrated the benefit of this technique on a simulated synthetic aperture sonar (SAS) dataset. We designed a machi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f2eae09e3cf7661724b438f656862b1
https://purehost.bath.ac.uk/ws/files/265031399/ICUA_2022_author_accepted_version.pdf

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Dirichlet Process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations

Autor: Tom S. F. Haines, Leo Singer, Archisman Ghosh, Alberto Vecchio, Christopher P. L. Berry, W. Del Pozzo

Publikováno v: Pozzo, W D, Berry, C P L, Ghosh, A, Haines, T S F & Vecchio, A 2018, ' Dirichlet Process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations ', Monthly Notices of the Royal Astronomical Society, vol. 479, no. 1, pp. 601-614 . https://doi.org/10.1093/mnras/sty1485

We reconstruct posterior distributions for the position (sky area and distance) of a simulated set of binary neutron-star gravitational-waves signals observed with Advanced LIGO and Advanced Virgo. We use a Dirichlet Process Gaussian-mixture model, a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::512132d9131a3930f93829e92b532d1e
http://hdl.handle.net/11568/923490

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My Text in Your Handwriting

Autor: Tom S. F. Haines, Oisin Mac Aodha, Gabriel J. Brostow

Publikováno v: Haines, T S F, Mac Aodha, O & Brostow, G J 2016, ' My Text in Your Handwriting ', ACM Transactions on Graphics, vol. 35, no. 3, 26, pp. 1-19 . https://doi.org/10.1145/2886099

There are many scenarios where we wish to imitate a specific author’s pen-on-paper handwriting style. Rendering new text in someone’s handwriting is difficult because natural handwriting is highly variable, yet follows both intentional and involu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e9e7429e4b4aab5bd0058a2d70300f3
https://purehost.bath.ac.uk/ws/files/157632649/my_text_in_your_handwriting.pdf

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Background Subtraction with DirichletProcess Mixture Models

Autor: Tao Xiang, Tom S. F. Haines

Publikováno v: Fincham Haines, T & Xiang, T 2013, ' Background Subtraction with Dirichlet Process Mixture Models ', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 4, pp. 670-683 . https://doi.org/10.1109/TPAMI.2013.239

Video analysis often begins with background subtraction. This problem is often approached in two steps - a background model followed by a regularisation scheme. A model of the background allows it to be distinguished on a per-pixel basis from the for

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bcbf13dd03b0d2354b8e118b227a2b3
https://pubmed.ncbi.nlm.nih.gov/26353192

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Background Subtraction with Dirichlet Processes

Autor: Tao Xiang, Tom S. F. Haines

Publikováno v: Computer Vision – ECCV 2012 ISBN: 9783642337642
ECCV (4)

Background subtraction is an important first step for video analysis, where it is used to discover the objects of interest for further processing. Such an algorithm often consists of a background model and a regularisation scheme. The background mode

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2859116b289f390d5107d963aac360ef
https://doi.org/10.1007/978-3-642-33765-9_8

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Delta-Dual Hierarchical Dirichlet Processes: A pragmatic abnormal behaviour detector

Autor: Tao Xiang, Tom S. F. Haines

Publikováno v: ICCV

In the security domain a key problem is identifying rare behaviours of interest. Training examples for these behaviours may or may not exist, and if they do exist there will be few examples, quite probably one. We present a novel weakly supervised al

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::53d9939d2fc6b23fa63461e7fb60a137
https://doi.org/10.1109/iccv.2011.6126497

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