BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

128 related articles for article (PubMed ID: 38870125)

  • 1. The attentive reconstruction of objects facilitates robust object recognition.
    Ahn S; Adeli H; Zelinsky GJ
    PLoS Comput Biol; 2024 Jun; 20(6):e1012159. PubMed ID: 38870125
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.
    Rajalingham R; Issa EB; Bashivan P; Kar K; Schmidt K; DiCarlo JJ
    J Neurosci; 2018 Aug; 38(33):7255-7269. PubMed ID: 30006365
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Beyond core object recognition: Recurrent processes account for object recognition under occlusion.
    Rajaei K; Mohsenzadeh Y; Ebrahimpour R; Khaligh-Razavi SM
    PLoS Comput Biol; 2019 May; 15(5):e1007001. PubMed ID: 31091234
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortex.
    Jia X; Hong H; DiCarlo JJ
    Elife; 2021 Jun; 10():. PubMed ID: 34114566
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition.
    Nayebi A; Sagastuy-Brena J; Bear DM; Kar K; Kubilius J; Ganguli S; Sussillo D; DiCarlo JJ; Yamins DLK
    Neural Comput; 2022 Jul; 34(8):1652-1675. PubMed ID: 35798321
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
    Spoerer CJ; McClure P; Kriegeskorte N
    Front Psychol; 2017; 8():1551. PubMed ID: 28955272
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A neurocomputational model of decision and confidence in object recognition task.
    Roshan SS; Sadeghnejad N; Sharifizadeh F; Ebrahimpour R
    Neural Netw; 2024 Jul; 175():106318. PubMed ID: 38643618
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Top-down attention based on object representation and incremental memory for knowledge building and inference.
    Kim B; Ban SW; Lee M
    Neural Netw; 2013 Oct; 46():9-22. PubMed ID: 23624577
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A brain-inspired object-based attention network for multiobject recognition and visual reasoning.
    Adeli H; Ahn S; Zelinsky GJ
    J Vis; 2023 May; 23(5):16. PubMed ID: 37212782
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Capturing the objects of vision with neural networks.
    Peters B; Kriegeskorte N
    Nat Hum Behav; 2021 Sep; 5(9):1127-1144. PubMed ID: 34545237
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Recurrent processing improves occluded object recognition and gives rise to perceptual hysteresis.
    Ernst MR; Burwick T; Triesch J
    J Vis; 2021 Dec; 21(13):6. PubMed ID: 34905052
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The anterior temporal cortex is a primary semantic source of top-down influences on object recognition.
    Chiou R; Lambon Ralph MA
    Cortex; 2016 Jun; 79():75-86. PubMed ID: 27088615
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The Dynamic Multisensory Engram: Neural Circuitry Underlying Crossmodal Object Recognition in Rats Changes with the Nature of Object Experience.
    Jacklin DL; Cloke JM; Potvin A; Garrett I; Winters BD
    J Neurosci; 2016 Jan; 36(4):1273-89. PubMed ID: 26818515
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Texture-like representation of objects in human visual cortex.
    Jagadeesh AV; Gardner JL
    Proc Natl Acad Sci U S A; 2022 Apr; 119(17):e2115302119. PubMed ID: 35439063
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Invariant recognition drives neural representations of action sequences.
    Tacchetti A; Isik L; Poggio T
    PLoS Comput Biol; 2017 Dec; 13(12):e1005859. PubMed ID: 29253864
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Visual Object Recognition: Do We (Finally) Know More Now Than We Did?
    Gauthier I; Tarr MJ
    Annu Rev Vis Sci; 2016 Oct; 2():377-396. PubMed ID: 28532357
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep Neural Networks and Visuo-Semantic Models Explain Complementary Components of Human Ventral-Stream Representational Dynamics.
    Jozwik KM; Kietzmann TC; Cichy RM; Kriegeskorte N; Mur M
    J Neurosci; 2023 Mar; 43(10):1731-1741. PubMed ID: 36759190
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Coherent interaction of dynamical attractors for object-based selective attention.
    Hoshino O
    Biol Cybern; 2003 Aug; 89(2):107-18. PubMed ID: 12905039
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mechanisms of human dynamic object recognition revealed by sequential deep neural networks.
    Sörensen LKA; Bohté SM; de Jong D; Slagter HA; Scholte HS
    PLoS Comput Biol; 2023 Jun; 19(6):e1011169. PubMed ID: 37294830
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Age-related changes in the neural dynamics of bottom-up and top-down processing during visual object recognition: an electrophysiological investigation.
    Lai LY; Frömer R; Festa EK; Heindel WC
    Neurobiol Aging; 2020 Oct; 94():38-49. PubMed ID: 32562874
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.