302 related articles for article (PubMed ID: 31036945)
1. Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.
Kar K; Kubilius J; Schmidt K; Issa EB; DiCarlo JJ
Nat Neurosci; 2019 Jun; 22(6):974-983. PubMed ID: 31036945
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks.
Xu Y; Vaziri-Pashkam M
J Neurosci; 2021 May; 41(19):4234-4252. PubMed ID: 33789916
[TBL] [Abstract][Full Text] [Related]
5. Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition.
Kar K; DiCarlo JJ
Neuron; 2021 Jan; 109(1):164-176.e5. PubMed ID: 33080226
[TBL] [Abstract][Full Text] [Related]
6. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.
Majaj NJ; Hong H; Solomon EA; DiCarlo JJ
J Neurosci; 2015 Sep; 35(39):13402-18. PubMed ID: 26424887
[TBL] [Abstract][Full Text] [Related]
7. Visual recognition in rhesus monkeys requires area TE but not TEO.
Eldridge MAG; Pearl JE; Fomani GP; Masseau EC; Fredericks JM; Chen G; Richmond BJ
Cereb Cortex; 2023 Mar; 33(6):3098-3106. PubMed ID: 35770336
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments.
Kalfas I; Vinken K; Vogels R
PLoS Comput Biol; 2018 Oct; 14(10):e1006557. PubMed ID: 30365485
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. A Critical Test of Deep Convolutional Neural Networks' Ability to Capture Recurrent Processing in the Brain Using Visual Masking.
Loke J; Seijdel N; Snoek L; van der Meer M; van de Klundert R; Quispel E; Cappaert N; Scholte HS
J Cogn Neurosci; 2022 Nov; 34(12):2390-2405. PubMed ID: 36122352
[TBL] [Abstract][Full Text] [Related]
12. Beyond the feedforward sweep: feedback computations in the visual cortex.
Kreiman G; Serre T
Ann N Y Acad Sci; 2020 Mar; 1464(1):222-241. PubMed ID: 32112444
[TBL] [Abstract][Full Text] [Related]
13. Deep convolutional models improve predictions of macaque V1 responses to natural images.
Cadena SA; Denfield GH; Walker EY; Gatys LA; Tolias AS; Bethge M; Ecker AS
PLoS Comput Biol; 2019 Apr; 15(4):e1006897. PubMed ID: 31013278
[TBL] [Abstract][Full Text] [Related]
14. Performance-optimized hierarchical models predict neural responses in higher visual cortex.
Yamins DL; Hong H; Cadieu CF; Solomon EA; Seibert D; DiCarlo JJ
Proc Natl Acad Sci U S A; 2014 Jun; 111(23):8619-24. PubMed ID: 24812127
[TBL] [Abstract][Full Text] [Related]
15. Orthogonal Representations of Object Shape and Category in Deep Convolutional Neural Networks and Human Visual Cortex.
Zeman AA; Ritchie JB; Bracci S; Op de Beeck H
Sci Rep; 2020 Feb; 10(1):2453. PubMed ID: 32051467
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.
Xu Y; Vaziri-Pashkam M
Neuroimage; 2022 Nov; 263():119635. PubMed ID: 36116617
[TBL] [Abstract][Full Text] [Related]
18. Encoding of Partially Occluded and Occluding Objects in Primate Inferior Temporal Cortex.
Namima T; Pasupathy A
J Neurosci; 2021 Jun; 41(26):5652-5666. PubMed ID: 34006588
[TBL] [Abstract][Full Text] [Related]
19. Predicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks.
Mocz V; Vaziri-Pashkam M; Chun M; Xu Y
J Cogn Neurosci; 2022 Nov; 34(12):2406-2435. PubMed ID: 36122358
[TBL] [Abstract][Full Text] [Related]
20. Deep neural networks rival the representation of primate IT cortex for core visual object recognition.
Cadieu CF; Hong H; Yamins DL; Pinto N; Ardila D; Solomon EA; Majaj NJ; DiCarlo JJ
PLoS Comput Biol; 2014 Dec; 10(12):e1003963. PubMed ID: 25521294
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
