Five images with the least recognition rate by human observers are displayed, respectively. The target categories are mainly sport and animal, with the smallest display size. In contrast to human performance, computational models are able to correctly recognize the respective categories in most of these images.</p
Discovering the visual features and representations used by the brain to recognize objects is a cent...
(a) Predicted probability of being an occlusion edge by the AO (blue curve). Image patches are sorte...
The topics discussed here are network models of object recognition; a computational theory of recogn...
Again, two scales are analyzed here: “L”- the largest level, “S”—the smallest level. SALIENCY model ...
These results were averaged from four target categories except the sport category due to the special...
<p> Colored dots correspond to the performance of the 4 computational models tested, black dots to t...
Recent advances in neural networks have revolutionized computer vision, but these algorithms are sti...
The predictions of 13 computational bottom-up saliency models and a newly introduced Multiscale Cont...
Computational or information-processing theories of vision describe object recognition in terms of a...
We demonstrate that human-vision-model-based image quality metrics not only correlate strongly with ...
International audienceIn this paper we compare a machine based semantic organisation of natural imag...
The human visual system is remarkably proficient at the task of identifying faces, even under severe...
This thesis presents a novel method of evaluating computational attention operators, which select lo...
Results at four levels of ISI values were showed for human observers. Three standard computational m...
We evaluated the adequacy of computational algo-rithms as models of human face processing by looking...
Discovering the visual features and representations used by the brain to recognize objects is a cent...
(a) Predicted probability of being an occlusion edge by the AO (blue curve). Image patches are sorte...
The topics discussed here are network models of object recognition; a computational theory of recogn...
Again, two scales are analyzed here: “L”- the largest level, “S”—the smallest level. SALIENCY model ...
These results were averaged from four target categories except the sport category due to the special...
<p> Colored dots correspond to the performance of the 4 computational models tested, black dots to t...
Recent advances in neural networks have revolutionized computer vision, but these algorithms are sti...
The predictions of 13 computational bottom-up saliency models and a newly introduced Multiscale Cont...
Computational or information-processing theories of vision describe object recognition in terms of a...
We demonstrate that human-vision-model-based image quality metrics not only correlate strongly with ...
International audienceIn this paper we compare a machine based semantic organisation of natural imag...
The human visual system is remarkably proficient at the task of identifying faces, even under severe...
This thesis presents a novel method of evaluating computational attention operators, which select lo...
Results at four levels of ISI values were showed for human observers. Three standard computational m...
We evaluated the adequacy of computational algo-rithms as models of human face processing by looking...
Discovering the visual features and representations used by the brain to recognize objects is a cent...
(a) Predicted probability of being an occlusion edge by the AO (blue curve). Image patches are sorte...
The topics discussed here are network models of object recognition; a computational theory of recogn...