Ha Hong
Ha Hong
Caption Health, Inc.; MIT
Bestätigte E-Mail-Adresse bei mit.edu
Titel
Zitiert von
Zitiert von
Jahr
Performance-optimized hierarchical models predict neural responses in higher visual cortex
DLK Yamins*, H Hong*, CF Cadieu, EA Solomon, D Seibert, JJ DiCarlo
Proceedings of the National Academy of Sciences 111 (23), 8619-8624, 2014
10012014
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition
CF Cadieu, H Hong, DLK Yamins, N Pinto, D Ardila, EA Solomon, ...
PLoS computational biology 10 (12), e1003963, 2014
4462014
Explicit information for category-orthogonal object properties increases along the ventral stream
H Hong*, DLK Yamins*, NJ Majaj, JJ DiCarlo
Nature neuroscience 19 (4), 613-622, 2016
1842016
Hierarchical modular optimization of convolutional networks achieves representations similar to macaque IT and human ventral stream
DL Yamins*, H Hong*, C Cadieu, JJ DiCarlo
Advances in neural information processing systems, 3093-3101, 2013
1172013
Simple learned weighted sums of inferior temporal neuronal firing rates accurately predict human core object recognition performance
NJ Majaj*, H Hong*, EA Solomon, JJ DiCarlo
The Journal of Neuroscience 35 (39), 13402-13418, 2015
932015
Flickering analysis of erythrocyte mechanical properties: dependence on oxygenation level, cell shape, and hydration level
YZ Yoon, H Hong, A Brown, DC Kim, DJ Kang, VL Lew, P Cicuta
Biophysical journal 97 (6), 1606-1615, 2009
752009
Brain-score: Which artificial neural network for object recognition is most brain-like?
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ...
BioRxiv, 407007, 2018
692018
The neural representation benchmark and its evaluation on brain and machine
CF Cadieu, H Hong, D Yamins, N Pinto, NJ Majaj, JJ DiCarlo
International Conference on Learning Representations (ICLR), 2013
282013
Brain-like object recognition with high-performing shallow recurrent ANNs
J Kubilius, M Schrimpf, K Kar, R Rajalingham, H Hong, N Majaj, E Issa, ...
Advances in Neural Information Processing Systems, 12805-12816, 2019
262019
Automated echocardiographic quantification of left ventricular ejection fraction without volume measurements using a machine learning algorithm mimicking a human expert
FM Asch, N Poilvert, T Abraham, M Jankowski, J Cleve, M Adams, ...
Circulation: Cardiovascular Imaging 12 (9), e009303, 2019
252019
A unified neuronal population code fully explains human object recognition
N Majaj, H Hong, E Solomon, JJ DiCarlo
Computational and Systems Neuroscience (COSYNE), 2012
72012
Guided navigation of an ultrasound probe
C Cadieu, H Hong, K Koepsell, J Mathe, M Wojtczyk
US Patent App. 15/831,375, 2018
62018
A performance-optimized model of neural responses across the ventral visual stream
D Seibert, D Yamins, D Ardila, H Hong, JJ DiCarlo, JL Gardner
bioRxiv, 036475, 2016
52016
Computational similarities between visual and auditory cortex studied with convolutional neural networks, fMRI, and electrophysiology
A Kell, D Yamins, S Norman-Haignere, D Seibert, H Hong, J DiCarlo, ...
Journal of vision 15 (12), 1093-1093, 2015
52015
Accuracy and reproducibility of a novel artificial intelligence deep learning-based algorithm for automated calculation of ejection fraction in echocardiography
FM Asch, T Abraham, M Jankowski, J Cleve, M Adams, N Romano, ...
Journal of the American College of Cardiology 73 (9S1), 1447-1447, 2019
42019
Deep Learning Algorithm for Fully-Automated Left Ventricular Ejection Fraction Measurement: P2-45
N Poilvert, H Hong, N Romano, D Adams, C Cadieu, R Bae, R Martin
Journal of the American Society of Echocardiography 31 (6), 2018
32018
Acquisition of diagnostic echocardiographic images by novices using a deep learning based image guidance algorithm
A Narang, R Bae, H Hong, Y Thomas, S Surette, C Cadieu, A Chaudhry, ...
Journal of the American College of Cardiology 75 (11S1), 1564-1564, 2020
22020
Using brain-score to evaluate and build neural networks for brain-like object recognition
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, C Ziemba, ...
Cosyne 19, Date: 2019/02/28-2019/03/03, Location: Lisbon, Portugal, 2019
22019
Artificially intelligent ejection fraction determination
C Cadieu, MG Cannon, H Hong, K Koepsell, J Mathe, N Poilvert
US Patent 10,470,677, 2019
12019
Innovative ultrasound technologies echogps and autoef help novices perform efficient and accurate echocardiographic monitoring in cancer patients
A Yen, AK Chaudhry, C Wang, X Tang, H Hong, N Poilvert, D Liang
Journal of the American College of Cardiology 73 (9S1), 1502-1502, 2019
12019
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