Visual Image Interpretation in Humans and Machines: Machines that see like us?
One Day BMVA symposium in London, UK on Wednesday 10th April, 2019
Registration closes 7th April 2019
Chair: Andrew Schofield
http://www.bmva.weebly.com
This one-day meeting will consider the issue in human and machine vision discussing how artificial neural net-works might be augmented with more biologically plausible features with the aim of making them more robust, and alternatives to neural network models and how their performance compares to the state of the art and human vision.
Programme:
9:10 Keynote: Charles Leek, University of Liverpool. "Deep Neural Networks: The new black box of human vision research?"
10:00 Thomas Tanay, University College London. "Built-in Vulnerabilities to Imperceptible Adversarial Perturbations".
10:15 Coffee.
10:30 Marin Dujmovic, University of Bristol, "Human performance on classification of fooling images".
10:45 Gaurav Malhotra, University of Bristol. "The contrasting roles of shape in human vision and convolutional neural networks".
11:00 Poster Session A Spotlights:
11:15 Posters and discussion.
12:00 Keynote: Tim Kietzmann, MRC CBU Cambridge. "Understanding vision at the interface of computational neuroscience and artificial intelligence".
12:45 Kai Kiwitz, Heinrich-Heine University, Dusseldorf. "Deep Learning Based Brain Mapping Resembles Human Brain Mapping"
13:00 Lunch
13:30 Ryan Blything, university of Bristol. "Translation Invariance in Vision: Evidence for On-line Generalization in Humans and Convolutional Neural Networks"
13:45 Javier Vazques Corral, University of East Anglia. "Are convolutional neural networks fooled by visual illusions?"
14:00 Poster Session B Spotlights.
14:15 Posters and discussion.
15:00 Keynote: Andrew Glennerster, University of Reading. "Policy networks with and without brains".
15:45 Julian Forrester, University of Essex. "Genetic Programming as an alternative to Neural Networks for Computer Vision".
16:00 Coffee
16:15 Marek Pedziwiatr, Cardiff University. "Meaning maps and deep neural networks are insensitive to semantic information when predicting human eye movements in natural scene viewing".
16:30 Ethan Harris, university of Southampton. "A Biologically Inspired Visual Working Memory for Deep Networks".
Registration:
Book online at http://www.bmva.org/meetings
BMVA Members £16, Non-Members £36, (Lunch Included)
Poster session A:
Fraser Smith, University of East Anglia, "Early visual regions in the human brain contain information about occluded parts of human faces".
Laszlo Talas, University of Bristol, "Modelling an evolutionarily arms-race with Generative Adversarial Networks"
John Harston, Imperial College London, "Body dynamics in ongoing tasks are predictive of visual attention"
Kofi Appiah, Sheffield Hallam University, "Mimicking the honeybee eyes for visual scene recognition".
Maija Filipovica, University of Birmingham, "Performance and scene area focus of human participants and neural networks in a visual stability discrimination task".
Alex Wade, University of York, "A neural correlate of DNN image classification confidence"
Poster session B:
Adar Pelah, University of York, "Clinical evaluation of machine learning approaches for the classification of 3D gait using static & dynamic models in comparison to human perception".
Frederick Stentiford, University College London, "Visual Recognition without Features or Training Data".
Wenshu Zhang, University of Southampton, "Understanding genetic variation by using automated measurement of shape".
Xiaoyue Jiang, Northwestern Polytechincal University, "Deep Shadow Detection and Removal"
Lindsay MacDonald, University College London, "Neural Networks for Colour Space Transformations"
Dr Andrew Schofield
Reader in Psychology
Life and Health Sciences
Birmingham, B4 7ET, UK
0121 204 3313
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www.aston.ac.uk
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