ReviewFrontiers in computational neuroscience2023
Convolutional neural networks for vision neuroscience: significance, developments, and outstanding issues.
Review in Frontiers in computational neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed.
- Brain-inspired energy efficient technologies for next-generation artificial intelligence.Biological cybernetics · 2026Review
- Clinical applications of deep learning in distinguishing benign from malignant pulmonary nodules in computed tomography scans.Archives of medical science : AMS · 2026Article
- Impact of a transient neonatal visual deprivation on the development of the ventral occipito-temporal cortex in humans.Nature communications · 2025Article
- Prediction of barberry witches' broom rust disease using artificial intelligence models: a case study in South Khorasan, Iran.Scientific reports · 2025Article
- Predicting PD-L1 status in NSCLC patients using deep learning radiomics based on CT images.Scientific reports · 2025Article
- Visual search and real-image similarity: An empirical assessment through the lens of deep learning.Psychonomic bulletin & review · 2025Article
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- NeoSLAM: Long-Term SLAM Using Computational Models of the Brain.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Convolutional Neural Networks (CNN) are a class of machine learning models predominately used in computer vision tasks and can achieve human-like performance through learning from experience. Their striking similarities to the structural and functional principles of the primate visual system allow for comparisons between these artificial networks and their biological counterparts, enabling exploration of how visual functions and neural representations may emerge in the real brain from a limited set of computational principles. After considering the basic features of CNNs, we discuss the opportunities and challenges of endorsing CNNs as
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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.