A model of active visual search with object-based attention guiding scan paths

Lanyon, Linda J.; Denham, Susan

doi:10.1016/j.neunet.2004.03.012

Cited by 55 publications

(81 citation statements)

References 119 publications

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“…For example, we are interested to see if the mechanisms described in (van der Velde & de ) can be applied to recent models of object recognition in the ventral stream, such as HMAX and more recent variations (Riesenhuber & Poggio, 1999;Serre, Wolf, Bileschi, Riesenhuber, & Poggio, 2007). Finally, we have observed that models of others are often very similar in mathematical structure (Lanyon & Denham, 2004;Usher & Niebur, 1996;Hamker, 2005), even when expressing ideas or models quite different from our own.…”

Section: The Need For Interoperability Of Modelsmentioning

confidence: 99%

“…Together with ANNs, Wilson-Cowan equations are one of the most widely used methods for cognitive neuroscience modelling (e.g., van der Velde & de Kamps, 2001;Lanyon & Denham, 2004;Usher & Niebur, 1996). Solving systems like Eq.…”

Section: Simulating Large Systems Of Coupled Equationsmentioning

confidence: 99%

“…In terms of modelling this entails interacting hierarchies of neural networks and the simulation of local neural circuits (van der Velde & de Kamps, 2001;de Kamps, 2005;van der Velde & de Kamps, 2006), usually in terms of rate models. Although there is a large number of models in cognitive neuroscience that all use the same, or very similar techniques, (see e.g., O'Reilly & Rudy, 2001;Lanyon & Denham, 2004;Usher & Niebur, 1996;Hamker, 2005;O'Reilly, 2006), Emergent (PDP++) is the only other software package that we are aware of at this level. Most models seem to be created from scratch and hence the situation in cognitive neuroscience is notably different from that in computational neuroscience.…”

Section: Miind In Relation With Other Neural Simulatorsmentioning

confidence: 99%

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The state of MIIND

et al. 2008

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MIIND (Multiple Interacting Instantiations of Neural Dynamics) is a highly modular multi-level C++ framework, that aims to shorten the development time for models in Cognitive Neuroscience (CNS). It offers reusable code modules (libraries of classes and functions) aimed at solving problems that occur repeatedly in modelling, but tries not to impose a specific modelling philosophy or methodology. At the lowest level, it offers support for the implementation of sparse networks. For example, the library SparseImplementationLib supports sparse random networks

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Section: The Need For Interoperability Of Modelsmentioning

confidence: 99%

Section: Simulating Large Systems Of Coupled Equationsmentioning

confidence: 99%

Section: Miind In Relation With Other Neural Simulatorsmentioning

confidence: 99%

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The state of MIIND

et al. 2008

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“…Many of the recent models perform object-based analysis for selective attention [17], [51], [52]. There are, however, only a few efforts which integrate spaceand object-based analysis in the same framework [4], [6], [7], [53].…”

Section: ) Space-and Object-based Analysismentioning

confidence: 99%

Visual Attention for Robotic Cognition: A Survey

Begum

Karray

2011

IEEE Trans. Auton. Mental Dev.

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Abstract-The goal of the cognitive robotics research is to design robots with human-like cognition (albeit reduced complexity) in perception, reasoning, action planning, and decision making. Such a venture of cognitive robotics has developed robots with redundant number of sensors and actuators in order to perceive the world and act up on it in a human-like fashion. A major challenge to deal with these robots is managing the enormous amount of information continuously arriving through multiple sensors.

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“…The lateral-intra parietal cortex (LIP) plays a role in providing a retinotopic spatio-feature map that is used to control the spatial focus of attention and fixation, which is able to integrate feature information in its spatial map (Lanyon & Denham, 2004). As an integrator of spatial and feature information, the LIP provides the inhibition of return (IOR) mechanism required here to prevent the scan path returning to previously inspected sites (Lanyon & Denham, 2004). Figure 5.…”

Section: Static Bottom-up Saliency Mapmentioning

confidence: 99%

Biologically Motivated Vergence Control System Based on Stereo Saliency Map Model

Ban¹

2007

Scene Reconstruction Pose Estimation and Tracking

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A model of active visual search with object-based attention guiding scan paths

Cited by 55 publications

References 119 publications

The state of MIIND

The state of MIIND

Visual Attention for Robotic Cognition: A Survey

Biologically Motivated Vergence Control System Based on Stereo Saliency Map Model

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