25 research outputs found
KINETICS OF AVAILABLE LYSINE LOSSES IN A SOY PROTEIN ISOLATE: CONFIRMATION OF THE 'TRANSITION PHASE' BY PROTEIN EFFICIENCY RATIO TESTS
An Adaptive Hierarchical Model of the Ventral Visual Pathway Implemented on a Mobile Robot
The implementation of an adaptive visual system founded on the detection of spatio-temporal invariances is described. It is a layered system inspired by the hierarchical processing in the mammalian ventral visual pathway, and models retinal, early cortical and infero-temporal components. A representation of scenes in terms of slowly varying spatiotemporal signatures is discovered through maximising a measure of temporal predictability. This supports categorisation of the environment by a set of view cells (view-trained units or VTUs [1]) that demonstrate substantial invariance to transformations of viewpoint and scale
Coupling of evolution and learning to optimize a hierarchical object recognition model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization methods can help to solve this problem. In this work we compare different evolutionary optimization approaches for a biologically inspired neural vision system: Direct coding versus a biologically more plausible indirect coding using unsupervised local learning. A comparison to state-of-the-art recognition approaches shows the competitiveness of our approach.
The representational–hierarchical view of pattern separation: Not just hippocampus, not just space, not just memory?
Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation
Public attitudes towards motorcyclists' safety: A qualitative study from the United Kingdom
The aim of the reported research was to examine the perceptions of road user safety amongst different road users and examine the link between attitudes, empathy and skill in motorcycle safety behaviour. Motorcyclists were perceived by the study participants, members of the public at four different locations at the UK (including motorcyclists and non-motorcyclists), as a group be at a high risk of accidents on the road. This was due to perceived behavioural characteristics of motorcyclists - who were viewed as 'thrill seekers' - as well as observed behaviours on the road. This, coupled with the physical vulnerability and excessive speeds, meant that motorbike driving was considered by the study participants as the least safe form of road use. There was broad agreement that motorcycling was dangerous as a whole, but not all motorcyclists were necessarily risky riders. The issue of 'competitive space' emerged between car drivers and motorcyclists in particular and it was suggested that there was a lack of mutual awareness and considerations between the two groups. Generally, greatest empathy comes from drivers who are motorcyclists themselves. Engineering, education, enforcement interventions were investigated. These were aimed at two main areas: normalising safer driving behaviours for motorcyclists and increasing awareness of bikes for motorists - particularly in relation to reducing speed limits at urban junctions. Finally, the idea of risk mapping and reduced speed limits on rural roads was seen as potentially effective - particularly as certain motorcyclists highlighted that they changed their riding behaviours by increasing speed and taking greater risks on these roads. © 2011 Elsevier Ltd