Literature DB >> 32027584

Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future.

Grace W Lindsay1.   

Abstract

Convolutional neural networks (CNNs) were inspired by early findings in the study of biological vision. They have since become successful tools in computer vision and state-of-the-art models of both neural activity and behavior on visual tasks. This review highlights what, in the context of CNNs, it means to be a good model in computational neuroscience and the various ways models can provide insight. Specifically, it covers the origins of CNNs and the methods by which we validate them as models of biological vision. It then goes on to elaborate on what we can learn about biological vision by understanding and experimenting on CNNs and discusses emerging opportunities for the use of CNNs in vision research beyond basic object recognition.

Year:  2020        PMID: 32027584     DOI: 10.1162/jocn_a_01544

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  32 in total

1.  A Model for Neural Network Modeling in Neuroscience.

Authors:  Katherine R Storrs; Guido Maiello
Journal:  J Neurosci       Date:  2020-09-09       Impact factor: 6.167

Review 2.  Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review.

Authors:  Benjamin Kompa; Joe B Hakim; Anil Palepu; Kathryn Grace Kompa; Michael Smith; Paul A Bain; Stephen Woloszynek; Jeffery L Painter; Andrew Bate; Andrew L Beam
Journal:  Drug Saf       Date:  2022-05-17       Impact factor: 5.606

3.  Integration of allocentric and egocentric visual information in a convolutional/multilayer perceptron network model of goal-directed gaze shifts.

Authors:  Parisa Abedi Khoozani; Vishal Bharmauria; Adrian Schütz; Richard P Wildes; J Douglas Crawford
Journal:  Cereb Cortex Commun       Date:  2022-07-08

4.  Structured random receptive fields enable informative sensory encodings.

Authors:  Biraj Pandey; Marius Pachitariu; Bingni W Brunton; Kameron Decker Harris
Journal:  PLoS Comput Biol       Date:  2022-10-10       Impact factor: 4.779

5.  Dementia in Convolutional Neural Networks: Using Deep Learning Models to Simulate Neurodegeneration of the Visual System.

Authors:  Jasmine A Moore; Anup Tuladhar; Zahinoor Ismail; Pauline Mouches; Matthias Wilms; Nils D Forkert
Journal:  Neuroinformatics       Date:  2022-09-09

6.  Asymmetry between right and left optical coherence tomography images identified using convolutional neural networks.

Authors:  Tae Seen Kang; Woohyuk Lee; Shin Hyeong Park; Yong Seop Han
Journal:  Sci Rep       Date:  2022-06-15       Impact factor: 4.996

7.  Film and Video Quality Optimization Using Attention Mechanism-Embedded Lightweight Neural Network Model.

Authors:  Youwen Ma
Journal:  Comput Intell Neurosci       Date:  2022-06-08

8.  Evaluation of Traditional Culture Teaching Efficiency by Course Ideological and Political Integration Lightweight Deep Learning.

Authors:  Qingqing Zhong
Journal:  Comput Intell Neurosci       Date:  2022-06-25

9.  Performance vs. competence in human-machine comparisons.

Authors:  Chaz Firestone
Journal:  Proc Natl Acad Sci U S A       Date:  2020-10-13       Impact factor: 11.205

10.  A Lightweight Multi-Scale Convolutional Neural Network for P300 Decoding: Analysis of Training Strategies and Uncovering of Network Decision.

Authors:  Davide Borra; Silvia Fantozzi; Elisa Magosso
Journal:  Front Hum Neurosci       Date:  2021-07-08       Impact factor: 3.169

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