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pro vyhledávání: '"David Peer"'
Convolutional Neural Networks (CNNs) have become the state of the art method for image classification in the last ten years. Despite the fact that they achieve superhuman classification accuracy on many popular datasets, they often perform much worse
Externí odkaz:
http://arxiv.org/abs/2001.10857
Autor:
Roger Martínez
Publikováno v:
International Sociology. 26:655-658
Autor:
Stephen Harrington
Publikováno v:
New Media & Society. 13:509-510
Autor:
Chris Engelhardt, Jakob Mittelberger, David Peer, Sebastian Stabinger, Antonio Rodríguez-Sánchez
Publikováno v:
2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS).
Fine-tuning transformer models after unsupervised pre-training reaches a very high performance on many different natural language processing tasks. Unfortunately, transformers suffer from long inference times which greatly increases costs in producti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a94f977467fe72eefd3a2f6221d05356
http://arxiv.org/abs/2105.14839
http://arxiv.org/abs/2105.14839
Publikováno v:
Pattern Recognition Letters
A recently proposed method in deep learning groups multiple neurons to capsules such that each capsule represents an object or part of an object. Routing algorithms route the output of capsules from lower-level layers to upper-level layers. In this p
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030863616
ICANN (1)
ICANN (1)
Capsule networks are a type of neural network that have recently gained increased popularity. They consist of groups of neurons, called capsules, which encode properties of objects or object parts. The connections between capsules encrypt part-whole
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e193f0cc5d4d7aec8a5a9cfcd773d136
https://doi.org/10.1007/978-3-030-86362-3_44
https://doi.org/10.1007/978-3-030-86362-3_44
Fine-tuning transformer models after unsupervised pre-training reaches a very high performance on many different NLP tasks. Unfortunately, transformers suffer from long inference times which greatly increases costs in production and is a limiting fac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b464021f3021c46cae6794d57a48f538
Publikováno v:
WACV
Designing neural network architectures is a challenging task and knowing which specific layers of a model must be adapted to improve the performance is almost a mystery. In this paper, we introduce a novel theory and metric to identify layers that de
Convolutional neural networks have established themselves over the past years as the state of the art method for image classification, and for many datasets, they even surpass humans in categorizing images. Unfortunately, the same architectures perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b8c7200a71d0f9cb378edce2211ad46