John Halpin -

E-mailjohn.halpinsams.acuk

Scottish Marine Institute
PA37 1QA Oban
United Kingdom

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Resultado de pesquisa por ano

Research Interests

I am a marine image analyst leading in this field at SAMS, with over four years’ experience in biological image analysis. I have previously worked at Cancer Research UK’s Beatson Institute developing custom image analysis pipelines, including deep learning methods with CNNs. I am currently leading the image analysis component of three projects, involving the latest techniques, such as custom deep learning pipelines for the automatic recognition of flora and fauna and photogrammetry/3D modelling.

Prior to working as an image analyst, I completed two Postdocs in advanced Transmission Electron Microscopy, which included developing new energy materials, and a PhD in semiconductor physics.

Experiência relacionada com os ODS da ONU

Em 2015, os estados membros da ONU concordaram com 17 Objetivos de Desenvolvimento Sustentável (ODS) globais para acabar com a pobreza, proteger o planeta e garantir a prosperidade para todos. O trabalho desta pessoa contribui para o(s) seguinte(s) ODS:

Good health and well being
Affordable and clean energy
Life below water

Impressão digital

Mergulhe nos tópicos de investigação onde John Halpin está ativo. Estas etiquetas de tópicos vêm dos trabalhos desta pessoa. Em conjunto formam uma impressão digital única.

6 Perfis semelhantes

23 Article
11 Conference contribution
1 Other report
1 Paper
Mais
- 1 Preprint

Bayesian multimodal fusion for seafloor habitat mapping with autonomous underwater vehicles
Morgan, T., Halpin, J. & Wilding, T. A., 1 out. 2026, Em: Engineering Applications of Artificial Intelligence. 181, 4, 15 p., 115340.
Resultado de pesquisa: Article › revisão de pares

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Ficheiro
3 Transferências (Pure)
Machine-assisted image analysis facilitates conservation of iconic elasmobranchs
Halpin, J., Marlow, J., Benjamins, S., Dodd, J., Gontarek, S. & Wilding, T. A., 11 mai. 2026, (E-pub ahead of print) Em: Ecological Solutions and Evidence. 7, 2, p. n/a - n/a 11 p.
Resultado de pesquisa: Article › revisão de pares

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Ficheiro
3 Transferências (Pure)
Preliminary evidence of intra-offshore wind farm variation in epibiotic assemblages from automated ROV image analysis
Marlow, J., Halpin, J. E. & Wilding, T. A., 1 ago. 2026, Em: Marine Environmental Research. 220, 108180.
Resultado de pesquisa: Article › revisão de pares

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Ficheiro
2 Transferências (Pure)
The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea
Bax, N., Halpin, J., Long, S., Yesson, C., Marlow, J. & Zwerschke, N., 1 jan. 2025, Em: Oceanography. 38, 1, p. 89-91 3 p.
Resultado de pesquisa: Article › revisão de pares

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Ficheiro
490 Transferências (Pure)
3D photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass
Marlow, J., Halpin, J. E. & Wilding, T. A., 26 mar. 2024, Em: Methods in Ecology and Evolution.
Resultado de pesquisa: Article › revisão de pares

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Ficheiro
11 Citações (Scopus)

220 Transferências (Pure)
Detection and characterisation of derelict creel fleets to evaluate marine megafauna entanglement risk in Scottish waters: CreelMap Final Project Report Scottish Marine Environmental Enhancement Fund (SMEEF) projects 502257 / 502492
Benjamins, S., Fox, C., Marlow, J., Halpin, J., Rybanska , P. & Howe, J., 9 out. 2024, 32 p.
Resultado de pesquisa: Other report

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Ficheiro
262 Transferências (Pure)
A Correlative Study of Interfacial Segregation in a Cu-Doped TiNiSn Thermoelectric half-Heusler Alloy
Halpin, J. E., Jenkins, B., Moody, M. P., Webster, R. W. H., Bos, J. W. G., Bagot, P. A. J. & Maclaren, D. A., 23 ago. 2022, Em: ACS Applied Electronic Materials. 4, 9, p. 4446-4454 9 p.
Resultado de pesquisa: Article › revisão de pares

Acesso aberto
Ficheiro
6 Citações (Scopus)

97 Transferências (Pure)

3D Photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass
Marlow, J. (Creator), Halpin, J. (Creator) & Wilding, T. (Creator), 6 mar. 2024
DOI: 10.5061/dryad.1rn8pk11z, https://pureadmin.uhi.ac.uk/admin/files/50149348/Methods_Ecol_Evol_-_2024_-_Marlow_-_3D_photogrammetry_and_deep_learning_deliver_accurate_estimates_of_epibenthic_biomass.pdf
Conjunto de dados: Dataset

John Halpin

Perfil pessoal

Research Interests

Experiência relacionada com os ODS da ONU

Impressão digital

Colaborações e principais áreas de investigação dos últimos cinco anos

Mergulhe nos detalhes

Bayesian multimodal fusion for seafloor habitat mapping with autonomous underwater vehicles

Machine-assisted image analysis facilitates conservation of iconic elasmobranchs

Preliminary evidence of intra-offshore wind farm variation in epibiotic assemblages from automated ROV image analysis

The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea

3D photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass

Detection and characterisation of derelict creel fleets to evaluate marine megafauna entanglement risk in Scottish waters: CreelMap Final Project Report Scottish Marine Environmental Enhancement Fund (SMEEF) projects 502257 / 502492

A Correlative Study of Interfacial Segregation in a Cu-Doped TiNiSn Thermoelectric half-Heusler Alloy

3D Photogrammetry and deep-learning deliver accurate estimates of epibenthic biomass

John Halpin

Perfil pessoal

Research Interests

Experiência relacionada com os ODS da ONU

Impressão digital

Colaborações e principais áreas de investigação dos últimos cinco anos

Resultado de pesquisa

Conjuntos de dados