ArticleFrontiers in computational neuroscience2014
Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems.
Article in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 26 citations in OpenAlex.
- Invariant visual object and face learning in the ventral cortical visual pathway: A biologically plausible model.PLoS computational biology · 2026Article
- Reduced spatial attentional distribution in older adults.Journal of vision · 2024Article
- Topography of inputs into the hippocampal formation of a food-caching bird.The Journal of comparative neurology · 2023Article
- Emotion, motivation, decision-making, the orbitofrontal cortex, anterior cingulate cortex, and the amygdala.Brain structure & function · 2023Review
- Hippocampal spatial view cells for memory and navigation, and their underlying connectivity in humans.Hippocampus · 2023Review
- Topography of inputs into the hippocampal formation of a food-caching bird.bioRxiv : the preprint server for biology · 2023Article
- Learning Invariant Object and Spatial View Representations in the Brain Using Slow Unsupervised Learning.Frontiers in computational neuroscience · 2021Review
- The visual development of hand-centered receptive fields in a neural network model of the primate visual system trained with experimentally recorded human gaze changes.Network (Bristol, England) · 2016Article
- Invariant visual object recognition: biologically plausible approaches.Biological cybernetics · 2015Article
- The Development of Hand-Centered Visual Representations in the Primate Brain: A Computer Modeling Study Using Natural Visual Scenes.Frontiers in computational neuroscience · 2015Article
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Authors and funding
2 authors at 2 institutions in 1 country.
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Abstract
Searching for and recognizing objects in complex natural scenes is implemented by multiple saccades until the eyes reach within the reduced receptive field sizes of inferior temporal cortex (IT) neurons. We analyze and model how the dorsal and ventral visual streams both contribute to this. Saliency detection in the dorsal visual system including area LIP is modeled by graph-based visual saliency, and allows the eyes to fixate potential objects within several degrees. Visual information at the fixated location subtending approximately 9° corresponding to the receptive fields of IT neurons is then passed through a four layer hierarchical model of the ventral cortical visual system, VisNet. We show that VisNet can be trained using a synaptic modification rule with a short-term memory trace of recent neuronal activity to capture both the required view and translation invariances to allow in the model approximately 90% correct object recognition for 4 objects shown in any view across a range of 135° anywhere in a scene. The model was able to generalize correctly within the four trained views and the 25 trained translations. This approach analyses the principles by which complementary computations in the dorsal and ventral visual cortical streams enable objects to be located and recognized in complex natural scenes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.