Zobrazeno 1 - 10
of 40
pro vyhledávání: '"David C. Noelle"'
Publikováno v:
Journal of Robotics, Vol 2011 (2011)
Traditional artificial neural network models of learning suffer from catastrophic interference. They are commonly trained to perform only one specific task, and, when trained on a new task, they forget the original task completely. It has been shown
Externí odkaz:
https://doaj.org/article/8b415a82a4d54c73a8a2979b375664d1
Autor:
David C. Noelle, Jeffrey Yoshimi
Publikováno v:
Mind, Cognition, and Neuroscience ISBN: 9781003241898
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca2f4fe789506f2bebd5501a11ca04df
https://doi.org/10.4324/9781003241898-11
https://doi.org/10.4324/9781003241898-11
Autor:
Trenton Kriete, David C Noelle
Publikováno v:
PLoS ONE, Vol 10, Iss 3, p e0121605 (2015)
Persons with autism regularly exhibit executive dysfunction (ED), including problems with deliberate goal-directed behavior, planning, and flexible responding in changing environments. Indeed, this array of deficits is sufficiently prominent to have
Externí odkaz:
https://doaj.org/article/d5a394d38f844a57afdcce83643edd2a
Autor:
David C. Noelle, Andrew L. Zimdars
Publikováno v:
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society ISBN: 9781410603494
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::968741ede316ca2780faeca7a85fec96
https://doi.org/10.4324/9781410603494-89
https://doi.org/10.4324/9781410603494-89
Autor:
Andreea Danielescu, David C. Noelle, Mohammad K. Ebrahimpour, Christopher T. Kello, Timothy M. Shea
Publikováno v:
ICASSP
Machine learning approaches to auditory object recognition are traditionally based on engineered features such as those derived from the spectrum or cepstrum. More recently, end-to-end classification systems in image and auditory recognition systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9411dacae396289c611c30c258716baa
http://arxiv.org/abs/2005.12195
http://arxiv.org/abs/2005.12195
Publikováno v:
IJCNN
We propose a new deep convolutional neural network framework that uses object location knowledge implicit in network connection weights to guide selective attention in object detection tasks. Our approach is called What-Where Nets (WW-Nets), and it i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62a627794e51186e477a0bb497bc8890
http://arxiv.org/abs/2005.07787
http://arxiv.org/abs/2005.07787
Autor:
Yen-Yun Yu, David C. Noelle, Azadeh Moghtaderi, Mohammad K. Ebrahimpour, Jackson Reesee, Ming-Hsuan Yang, Jiayun Li
Publikováno v:
WACV
Deep Convolutional Neural Networks (CNNs) have been repeatedly proven to perform well on image classification tasks. Object detection methods, however, are still in need of significant improvements. In this paper, we propose a new framework called Ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90cdc5bb8dd28cdacf1ec661dcb3b326
Publikováno v:
Cognitive Science. 43
Rich sensorimotor interaction facilitates language learning and is presumed to ground conceptual representations. Yet empirical support for early stages of embodied word learning is currently lacking. Finding evidence that sensorimotor interaction sh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70d63cb9d4af58d8cf74c74200d54b28
https://doi.org/10.1111/cogs.12742
https://doi.org/10.1111/cogs.12742
Publikováno v:
Advances in Visual Computing ISBN: 9783030337223
ISVC (2)
ISVC (2)
Deep Convolutional Neural Networks (CNNs) have recently begun to exhibit human level performance on some visual perception tasks. Performance remains relatively poor, however, on some vision tasks, such as object detection: specifying the location an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc07452a2ecd87a1622af3ef502d0004
https://doi.org/10.1007/978-3-030-33723-0_5
https://doi.org/10.1007/978-3-030-33723-0_5
Publikováno v:
Advances in Visual Computing ISBN: 9783030337223
ISVC (2)
ISVC (2)
Deep Convolutional Neural Networks (CNNs) have been repeatedly shown to perform well on image classification tasks, successfully recognizing a broad array of objects when given sufficient training data. Methods for object localization, however, are s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfe5049fd8997c99dae7052e1865f210
https://doi.org/10.1007/978-3-030-33723-0_17
https://doi.org/10.1007/978-3-030-33723-0_17