ArticleFrontiers in psychology2017
Perception Science in the Age of Deep Neural Networks.
Article in Frontiers in psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Making sense of transformer success.Frontiers in artificial intelligence · 2025Article
- Convolutional neural networks develop major organizational principles of early visual cortex when enhanced with retinal sampling.Scientific reports · 2024Article
- Predictive processing of scenes and objects.Nature reviews psychology · 2024Article
- Feature blindness: A challenge for understanding and modelling visual object recognition.PLoS computational biology · 2022Article
- Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model.PLoS computational biology · 2022Article
- Gloss perception: Searching for a deep neural network that behaves like humans.Journal of vision · 2021Article
- A comparative biology approach to DNN modeling of vision: A focus on differences, not similarities.Journal of vision · 2021Article
- Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?Cognitive science · 2021Article
- A deep-learning framework for human perception of abstract art composition.Journal of vision · 2021Article
- Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning.Scientific reports · 2020Article
- Challenges and Future Directions of Big Data and Artificial Intelligence in Education.Frontiers in psychology · 2020Review
- Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.Nature communications · 2019Article
- Reconstructing faces from fMRI patterns using deep generative neural networks.Communications biology · 2019Article
- In Praise of Artifice Reloaded: Caution With Natural Image Databases in Modeling Vision.Frontiers in neuroscience · 2019Article
- An oscillatory neural network model that demonstrates the benefits of multisensory learning.Cognitive neurodynamics · 2018Article
- Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.Frontiers in psychology · 2018Article
- Computational Foundations of Natural Intelligence.Frontiers in computational neuroscience · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.