Dr Joe MacInnes

Uwch-ddarlithydd

Computer Science

william.macinnes@abertawe.ac.uk

308
Trydydd Llawr
Y Ffowndri Gyfrifiadol
Campws y Bae

Ar gael ar gyfer Goruchwyliaeth Ôl-raddedig

Dolenni Ymchwil

https://orcid.org/0000-0002-5134-1601

Google Scholar

Trosolwg

Rwy'n ymchwilydd rhyngddisgyblaethol sydd â diddordeb mewn sut y defnyddir sylw i flaenoriaethu mewnbwn synhwyraidd er mwyn cwrdd â nodau asiant. Mae Seicoleg a niwrowyddoniaeth wedi astudio sylw mewn bodau dynol dros fwy na chanrif, ond mae sylw wedi dod o ddiddordeb i'r gymuned dysgu peirianyddol yn ddiweddar. Nod gyffredinol fy ymchwil yw deall sylw golygol trwy ddatblygu modelau dysgu peirianyddol sy'n efelychu prosesu golygol mewn bodau dynol. Rwy'n defnyddio data o dracio symudiadau cyflymder uchel y llygaid ac arbrofion sy'n cynnwys tasgau golygol cymhleth megis porthianna, chwilio a chofio golygfeydd er mwyn deall sut y defnyddir sylw, a hyfforddi modelau cyfrifiadurol i wneud tasgau tebyg. Wrth ddeall sylw dynol yn well, rydym hefyd yn dysgu ffyrdd newydd o feddwl am sylw peirianyddol, a'i rhoi ar waith.

Meysydd Arbenigedd

Dysgu peirianyddol
Sylw
Tracio symudiadau llygaid
Chwilio golygol
Modelu Gwybyddol Cyfrifiadurol
Deallusrwydd artiffisial
Ataliad dychwelyd (Inhibition of return)

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Redden, R., MacInnes, J., & Klein, R. (2021). Inhibition of return: An information processing theory of its natures and significance. Cortex, 135, 30-48.
https://doi.org/10.1016/j.cortex.2020.11.009, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63436
http://dx.doi.org/10.1016/j.cortex.2020.11.009
Dreneva, A., Chernova, U., Ermolova, M., & MacInnes, J. (2021). Attention Trade-Off for Localization and Saccadic Remapping. Vision, 5(2), 24
https://doi.org/10.3390/vision5020024, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63435
http://dx.doi.org/10.3390/vision5020024
Gorina, E., Kulikova, A., & MacInnes, J. (2021). Comparing saccadic and manual responses in the attention network test. Cortex, 144, 29-42.
https://doi.org/10.1016/j.cortex.2021.07.014, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63434
http://dx.doi.org/10.1016/j.cortex.2021.07.014
Zemliak, V. & MacInnes, J. (n.d.) The Spatial Leaky Competing Accumulator Model. Frontiers in Computer Science, 4
https://doi.org/10.3389/fcomp.2022.866029, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63433
http://dx.doi.org/10.3389/fcomp.2022.866029
Nadezhda, M., Dovbnyuk, K., Merzon, L., & MacInnes, J. (2022). Between the Scenes. Experimental Psychology, 69(4), 185-195.
https://doi.org/10.1027/1618-3169/a000556, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63432
http://dx.doi.org/10.1027/1618-3169/a000556
Le, S., Kristjánsson, Á., & MacInnes, J. (2023). Bayesian approximations to the theory of visual attention (TVA) in a foraging task. Quarterly Journal of Experimental Psychology, 76(3), 497-510.
https://doi.org/10.1177/17470218221094572, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63429
http://dx.doi.org/10.1177/17470218221094572
Merzon, L., Pettersson, K., Aronen, E., Huhdanpää, H., Seesjärvi, E., Henriksson, L., MacInnes, J., Mannerkoski, M., Macaluso, E., & Salmi, J. (2022). Eye movement behavior in a real-world virtual reality task reveals ADHD in children. Scientific Reports, 12(1)
https://doi.org/10.1038/s41598-022-24552-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63400
Krasovskaya, S., Zhulikov, G., & MacInnes, J. (n.d.) Deep Learning Neural Networks as a Model of Saccadic Generation. SSRN Electronic Journal
https://doi.org/10.2139/ssrn.3262650, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63401
http://dx.doi.org/10.2139/ssrn.3262650
MacInnes, J., Jóhannesson, Ó., Chetverikov, A., & Kristjánsson, Á. (2020). No Advantage for Separating Overt and Covert Attention in Visual Search. Vision, 4(2), 28
https://doi.org/10.3390/vision4020028, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63403
http://dx.doi.org/10.3390/vision4020028
Malevich, T., Rybina, E., Ivtushok, E., Ardasheva, L., MacInnes, W., & MacInnes, J. (2020). No evidence for an independent retinotopic reference frame for inhibition of return. Acta Psychologica, 208, 103107
https://doi.org/10.1016/j.actpsy.2020.103107, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63404
http://dx.doi.org/10.1016/j.actpsy.2020.103107

Holl Ymchwil

Erthyglau Cylchgronau

Le, S., Kristjánsson, Á., & MacInnes, J. (2024). Target selection during “snapshot” foraging. Attention, Perception, & Psychophysics, 86(8), 2778-2793.
https://doi.org/10.3758/s13414-024-02988-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68531
Salmi, J., Merzon, L., Eräste, T., Seesjärvi, E., Huhdanpää, H., Aronen, E., Mannerkoski, M., MacInnes, J., & Laine, M. (2024). Fluctuations of Attention During Self-paced Naturalistic Goal-Directed Behavior in Attention-Deficit/Hyperactivity Disorder. JAACAP Open, 2(3), 188-198.
https://doi.org/10.1016/j.jaacop.2023.12.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68412
Le, S., Kristjánsson, Á., & MacInnes, J. (2023). Bayesian approximations to the theory of visual attention (TVA) in a foraging task. Quarterly Journal of Experimental Psychology, 76(3), 497-510.
https://doi.org/10.1177/17470218221094572, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63429
http://dx.doi.org/10.1177/17470218221094572
Merzon, L., Pettersson, K., Aronen, E., Huhdanpää, H., Seesjärvi, E., Henriksson, L., MacInnes, J., Mannerkoski, M., Macaluso, E., & Salmi, J. (2022). Eye movement behavior in a real-world virtual reality task reveals ADHD in children. Scientific Reports, 12(1)
https://doi.org/10.1038/s41598-022-24552-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63400
Murziakova, N., Dovbnyuk, K., & MacInnes, J. (2022). Correction to Murziakova et al., 2022. Experimental Psychology, 69(6), 351-351.
https://doi.org/10.1027/1618-3169/a000570, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63431
http://dx.doi.org/10.1027/1618-3169/a000570
Nadezhda, M., Dovbnyuk, K., Merzon, L., & MacInnes, J. (2022). Between the Scenes. Experimental Psychology, 69(4), 185-195.
https://doi.org/10.1027/1618-3169/a000556, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63432
http://dx.doi.org/10.1027/1618-3169/a000556
Gorina, E., Kulikova, A., & MacInnes, J. (2021). Comparing saccadic and manual responses in the attention network test. Cortex, 144, 29-42.
https://doi.org/10.1016/j.cortex.2021.07.014, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63434
http://dx.doi.org/10.1016/j.cortex.2021.07.014
Dreneva, A., Chernova, U., Ermolova, M., & MacInnes, J. (2021). Attention Trade-Off for Localization and Saccadic Remapping. Vision, 5(2), 24
https://doi.org/10.3390/vision5020024, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63435
http://dx.doi.org/10.3390/vision5020024
Redden, R., MacInnes, J., & Klein, R. (2021). Inhibition of return: An information processing theory of its natures and significance. Cortex, 135, 30-48.
https://doi.org/10.1016/j.cortex.2020.11.009, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63436
http://dx.doi.org/10.1016/j.cortex.2020.11.009
Malevich, T., Rybina, E., Ivtushok, E., Ardasheva, L., MacInnes, W., & MacInnes, J. (2020). No evidence for an independent retinotopic reference frame for inhibition of return. Acta Psychologica, 208, 103107
https://doi.org/10.1016/j.actpsy.2020.103107, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63404
http://dx.doi.org/10.1016/j.actpsy.2020.103107
MacInnes, J., Jóhannesson, Ó., Chetverikov, A., & Kristjánsson, Á. (2020). No Advantage for Separating Overt and Covert Attention in Visual Search. Vision, 4(2), 28
https://doi.org/10.3390/vision4020028, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63403
http://dx.doi.org/10.3390/vision4020028
Merzon, L., Malevich, T., Zhulikov, G., Krasovskaya, S., & MacInnes, J. (2020). Temporal Limitations of the Standard Leaky Integrate and Fire Model. Brain Sciences, 10(1), 16
https://doi.org/10.3390/brainsci10010016, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63406
http://dx.doi.org/10.3390/brainsci10010016
Krasovskaya, S. & MacInnes, J. (2019). Salience Models: A Computational Cognitive Neuroscience Review. Vision, 3(4), 56
https://doi.org/10.3390/vision3040056, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63407
http://dx.doi.org/10.3390/vision3040056
MacInnes, J., Hunt, A., Clarke, A., & Dodd, M. (2018). A Generative Model of Cognitive State from Task and Eye Movements. Cognitive Computation, 10(5), 703-717.
https://doi.org/10.1007/s12559-018-9558-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63408
http://dx.doi.org/10.1007/s12559-018-9558-9
Chetverikov, A., Kuvaldina, M., MacInnes, W., Jóhannesson, Ó., Kristjánsson, Á., & MacInnes, J. (2018). Implicit processing during change blindness revealed with mouse-contingent and gaze-contingent displays. Attention, Perception, & Psychophysics, 80(4), 844-859.
https://doi.org/10.3758/s13414-017-1468-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63411
http://dx.doi.org/10.3758/s13414-017-1468-5
Malevich, T., Ardasheva, L., Krüger, H., & MacInnes, J. (2018). Temporal ambiguity of onsets in a cueing task prevents facilitation but not inhibition of return. Attention, Perception, & Psychophysics, 80(1), 106-117.
https://doi.org/10.3758/s13414-017-1435-1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63412
http://dx.doi.org/10.3758/s13414-017-1435-1
MacInnes, J. (2017). Multiple Diffusion Models to Compare Saccadic and Manual Responses for Inhibition of Return. Neural Computation, 29(3), 804-824.
https://doi.org/10.1162/neco_a_00904, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63413
http://dx.doi.org/10.1162/neco_a_00904
MacInnes, J., Krüger, H., & Hunt, A. (2015). Just passing through? Inhibition of return in saccadic sequences. Quarterly Journal of Experimental Psychology, 68(2), 402-416.
https://doi.org/10.1080/17470218.2014.945097, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63414
http://dx.doi.org/10.1080/17470218.2014.945097
MacInnes, J. & Hunt, A. (2014). Attentional load interferes with target localization across saccades. Experimental Brain Research, 232(12), 3737-3748.
https://doi.org/10.1007/s00221-014-4062-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63415
http://dx.doi.org/10.1007/s00221-014-4062-2
Kruger, H., MacInnes, W., Hunt, A., & MacInnes, J. (2014). Perceptual merging contributes to cueing effects. Journal of Vision, 14(7), 13-13.
https://doi.org/10.1167/14.7.13, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63417
http://dx.doi.org/10.1167/14.7.13
MacInnes, J., Hunt, A., Hilchey, M., & Klein, R. (2014). Driving forces in free visual search: An ethology. Attention, Perception, & Psychophysics, 76(2), 280-295.
https://doi.org/10.3758/s13414-013-0608-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63416
http://dx.doi.org/10.3758/s13414-013-0608-9
MacInnes, J. (2010). Computational evidence that word co-occurrence models predict turing test humanness judgments.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63418
MacInnes, J., Santosa, S., Wright, W., & MacInnes, J. (2010). Visual Classification: Expert Knowledge Guides Machine Learning. IEEE Computer Graphics and Applications, 30(1), 8-14.
https://doi.org/10.1109/mcg.2010.18, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63419
http://dx.doi.org/10.1109/mcg.2010.18
MacInnes, J. & Klein, R. (2003). Inhibition of Return Biases Orienting During the Search of Complex Scenes. The Scientific World JOURNAL, 3, 75-86.
https://doi.org/10.1100/tsw.2003.03, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63425
http://dx.doi.org/10.1100/tsw.2003.03
MacInnes, J. & Taylor, T. (2001). Millisecond timing on PCs and Macs. Behavior Research Methods, Instruments, & Computers, 33(2), 174-178.
https://doi.org/10.3758/bf03195363, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63426
http://dx.doi.org/10.3758/bf03195363
SHORE, D., STANFORD, L., MacInnes, J., KLEIN, R., & BROWN, R. (2001). Of mice and men: Virtual Hebb-Williams mazes permit comparison of spatial learning across species. Cognitive, Affective, & Behavioral Neuroscience, 1(1), 83-89.
https://doi.org/10.3758/cabn.1.1.83, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63427
http://dx.doi.org/10.3758/cabn.1.1.83
Klein, R. & MacInnes, J. (1999). Inhibition of Return is a Foraging Facilitator in Visual Search. Psychological Science, 10(4), 346-352.
https://doi.org/10.1111/1467-9280.00166, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63428
http://dx.doi.org/10.1111/1467-9280.00166
Zemliak, V. & MacInnes, J. (n.d.) The Spatial Leaky Competing Accumulator Model. Frontiers in Computer Science, 4
https://doi.org/10.3389/fcomp.2022.866029, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63433
http://dx.doi.org/10.3389/fcomp.2022.866029
Krasovskaya, S., Zhulikov, G., & MacInnes, J. (n.d.) Deep Learning Neural Networks as a Model of Saccadic Generation. SSRN Electronic Journal
https://doi.org/10.2139/ssrn.3262650, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63401
http://dx.doi.org/10.2139/ssrn.3262650
MacInnes, J. & Bhatnagar, R. (n.d.) No supplementary evidence of attention to a spatial cue when saccadic facilitation is absent. Scientific Reports, 8(1)
https://doi.org/10.1038/s41598-018-31633-w, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63409
http://dx.doi.org/10.1038/s41598-018-31633-w
Krasovskaya, S., Kristjánsson, Á., & MacInnes, J. (n.d.) Microsaccade rate activity during the preparation of pro- and antisaccades. Attention, Perception, & Psychophysics
https://doi.org/10.3758/s13414-023-02731-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63626
http://dx.doi.org/10.3758/s13414-023-02731-3

Cyfraniadau Cynadleddau

HUMAIDAN, A., Roy, J., Sharifzadeh, S., Mehta, R., Tales, A., & MacInnes, J. (2025). Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model. In 2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion) (pp. 1-5). IEEE.
https://doi.org/10.1109/cismcompanion65074.2025.11032695, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa69135
MacInnes, J., Zhozhikashvili, N., & Feurra, M. (2024). Weight Perturbations for Simulating Virtual Lesions in a Convolutional Neural Network. In Lecture Notes in Computer Science (pp. 221-234). Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-67285-9_16, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa69412

Goruchwyliaeth

Untitled (cyfredol)

PhD

Goruchwyliwr arall: Prof Jiaxiang Zhang
Untitled (cyfredol)

PhD

Goruchwyliwr arall: Dr Scott Yang
Untitled (cyfredol)

PhD

Goruchwyliwr arall: Dr Sara Sharifzadeh
Leveraging Advanced Imaging Techniques and Distributed Systems for Enhanced Lung Cancer Treatment Pathways with Variable Data Modeling (cyfredol)

PhD

Goruchwyliwr arall: Prof Jiaxiang Zhang
Old title: Measures of Visual Dispersion in relation to Attention. New Title: How Attention and Eye Movement change with different tasks (cyfredol)

PhD

Goruchwyliwr arall: Dr Sara Sharifzadeh
AI-Driven Anomaly Detection in Human Activity Monitoring Systems for Enhancing Health and Well-being Tracking (cyfredol)

PhD

Goruchwyliwr arall: Dr Sara Sharifzadeh
Machine Networks of Attention from Human Networks of Attention (cyfredol)

PhD

Goruchwyliwr arall: Prof Xianghua Xie
Investigating Textual Ambiguity using Computational Linguistics. (cyfredol)

PhD

Goruchwyliwr arall: Dr Nicholas Micallef
Advancements in Detection Methods using Attention, Multi-Modalities, and Exploitable Cues. (cyfredol)

PhD

Goruchwyliwr arall: Dr Gary Tam

Modiwlau a Addysgir

CSC357 Brain-Inspired Artificial Intelligence

This module investigates developments in Psychology and Neuroscience that have led to various state-of-the-art Machine Learning techniques and how these relate to more traditional approaches in Computer Science.
CSCM02ON Database Systems & Web Apps (April)

This module provides a comprehensive introduction to database and web application development, starting with the relational model and SQL for data manipulation and definition. Students will learn design principles, normalisation, and data integrity, along with entity and dependency diagrams. The curriculum covers optimisation, relational algebra, and views, as well as concurrency, security, and authentication. Key topics include transactions and recovery, UX and web programming principles, and HTML, CSS, forms, and frameworks. The module also explores 'convention over configuration', migrations, models, relationships, MVC and Laravel setup, and MVC-driven web applications. Practical skills in seeding, factories, CRUD operations, controllers, views, creating data, debugging, and routing are also developed.
CSCM759 Database Systems & Web Apps

This module provides a comprehensive introduction to database and web application development, starting with the relational model and SQL for data manipulation and definition. Students will learn design principles, normalisation, and data integrity, along with entity and dependency diagrams. The curriculum covers optimisation, relational algebra, and views, as well as concurrency, security, and authentication. Key topics include transactions and recovery, UX and web programming principles, and HTML, CSS, forms, and frameworks. The module also explores 'convention over configuration', migrations, models, relationships, MVC and Laravel setup, and MVC-driven web applications. Practical skills in seeding, factories, CRUD operations, controllers, views, creating data, debugging, and routing are also developed.
CSGD00 Taught Masters Dissertation (Computer Science:Informatique)

This module will provide students with the opportunity of exploring a particular topic in computer science in some considerable depth. It is only open to students studying MSc Computer Science, MSc Advanced Computer Science, MSc Advanced Software Technology or the MSc in High Performance and Scientific Computing.
CSGM01 Dual Award Swansea Grenoble MSc - Semester

This module aggregates the Semester 1 (French: Semestre 7) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of six compulsory topics related to technical computer science, as well as material on technical writing and a four-week programming project.
CSGM02 Dual Award Swansea Grenoble MSc - Semester 2

This module aggregates the Semester 2 (French: Semestre 8) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory topics related to research preparation; and a choice of seven of 12 technical topics (see syllabus for details).
CSGM31 Dual Award Swansea Grenoble MSc - Semester 3 - Advanced Information Systems and Software Engineering

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of six compulsory and three optional technical topics related to the fields of Advanced Information Systems and Software Engineering.
CSGM32 Dual Award Swansea Grenoble MSc - Semester 3 - AI and the Web

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and 4 (of 5) optional technical topics related to AI and the Web.
CSGM33 Dual Award Swansea Grenoble MSc - Semester 3 - Graphics, Vision and Robotics

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory and three optional technical topics related to the fields of Graphics, Vision and Robotics.
CSGM34 Dual Award Swansea Grenoble MSc - Semester 3 - Data Science

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of eight compulsory and three optional technical topics related to the field of Data Science.
CSGM35 Dual Award Swansea Grenoble MSc - Semester 3 - High-confidence Embedded and Cyberphysical Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of three compulsory and three optional technical topics related to the fields of High-confidence Embedded and Cyberphysical Systems.
CSGM36 Dual Award Swansea Grenoble MSc - Semester 3 - Parallel, Distributed and Embedded Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and three optional technical topics related to the fields of Parallel, Distributed and Embedded Systems.
CSGM37 Dual Award Swansea Grenoble MSc - Semester 3 - Ubiquitous and Interactive Systems

This module aggregates the Semester 3 (French: Semestre 9) modules that form part of the Grenoble delivery of the Dual Award MSc in Informatics. The module consists of four compulsory and three optional technical topics related to the fields of Ubiquitous and Interactive Systems.
CSGM40 Dual Award Swansea Grenoble MSc - Semester 4 - Project

This module represents a substantial scientific research project undertaken at Universite Grenoble Alpes as part of the Dual Degree MSc in Informatics.

Dr Joe MacInnes

Cyfeiriad ebost

Dolenni Ymchwil

Trosolwg

Meysydd Arbenigedd

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Holl Ymchwil

Erthyglau Cylchgronau

Cyfraniadau Cynadleddau

Goruchwyliaeth

Untitled (cyfredol)

Untitled (cyfredol)

Untitled (cyfredol)

Leveraging Advanced Imaging Techniques and Distributed Systems for Enhanced Lung Cancer Treatment Pathways with Variable Data Modeling (cyfredol)

Old title: Measures of Visual Dispersion in relation to Attention. New Title: How Attention and Eye Movement change with different tasks (cyfredol)

AI-Driven Anomaly Detection in Human Activity Monitoring Systems for Enhancing Health and Well-being Tracking (cyfredol)

Machine Networks of Attention from Human Networks of Attention (cyfredol)

Investigating Textual Ambiguity using Computational Linguistics. (cyfredol)

Advancements in Detection Methods using Attention, Multi-Modalities, and Exploitable Cues. (cyfredol)

Modiwlau a Addysgir

CSC357 Brain-Inspired Artificial Intelligence

CSCM02ON Database Systems & Web Apps (April)

CSCM759 Database Systems & Web Apps

CSGD00 Taught Masters Dissertation (Computer Science:Informatique)

CSGM01 Dual Award Swansea Grenoble MSc - Semester

CSGM02 Dual Award Swansea Grenoble MSc - Semester 2

CSGM31 Dual Award Swansea Grenoble MSc - Semester 3 - Advanced Information Systems and Software Engineering

CSGM32 Dual Award Swansea Grenoble MSc - Semester 3 - AI and the Web

CSGM33 Dual Award Swansea Grenoble MSc - Semester 3 - Graphics, Vision and Robotics

CSGM34 Dual Award Swansea Grenoble MSc - Semester 3 - Data Science

CSGM35 Dual Award Swansea Grenoble MSc - Semester 3 - High-confidence Embedded and Cyberphysical Systems

CSGM36 Dual Award Swansea Grenoble MSc - Semester 3 - Parallel, Distributed and Embedded Systems

CSGM37 Dual Award Swansea Grenoble MSc - Semester 3 - Ubiquitous and Interactive Systems

CSGM40 Dual Award Swansea Grenoble MSc - Semester 4 - Project