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pro vyhledávání: '"Herzog, Michael"'
Autor:
Vaughan, Anna, Markou, Stratis, Tebbutt, Will, Requeima, James, Bruinsma, Wessel P., Andersson, Tom R., Herzog, Michael, Lane, Nicholas D., Chantry, Matthew, Hosking, J. Scott, Turner, Richard E.
Weather forecasting is critical for a range of human activities including transportation, agriculture, industry, as well as the safety of the general public. Machine learning models have the potential to transform the complex weather prediction pipel
Externí odkaz:
http://arxiv.org/abs/2404.00411
Humans are able to segment images effortlessly without supervision using perceptual grouping. In this work, we propose a counter-intuitive computational approach to solving unsupervised perceptual grouping and segmentation: that they arise \textit{be
Externí odkaz:
http://arxiv.org/abs/2309.16515
Autor:
Herzog, Michael
Titre de l'écran-titre (visionné le 4 décembre 2023)
À l'échelle mondiale, les zones de cisaillement sont les plus importants hôtes de minéralisation aurifère de type « or orogénique ». Ces failles fragiles-ductiles sont la conséquen
À l'échelle mondiale, les zones de cisaillement sont les plus importants hôtes de minéralisation aurifère de type « or orogénique ». Ces failles fragiles-ductiles sont la conséquen
Externí odkaz:
http://hdl.handle.net/20.500.11794/130903
Deep learning models often face challenges when handling real-world image corruptions. In response, researchers have developed image corruption datasets to evaluate the performance of deep neural networks in handling such corruptions. However, these
Externí odkaz:
http://arxiv.org/abs/2306.07178
Convolutional neural networks (CNNs) have achieved superhuman performance in multiple vision tasks, especially image classification. However, unlike humans, CNNs leverage spurious features, such as background information to make decisions. This tende
Externí odkaz:
http://arxiv.org/abs/2210.02748
In a recent article, Guo et al. [arXiv:2206.11228] report that adversarially trained neural representations in deep networks may already be as robust as corresponding primate IT neural representations. While we find the paper's primary experiment ill
Externí odkaz:
http://arxiv.org/abs/2208.01456
Deep convolutional neural networks (DCNNs) have revolutionized computer vision and are often advocated as good models of the human visual system. However, there are currently many shortcomings of DCNNs, which preclude them as a model of human vision.
Externí odkaz:
http://arxiv.org/abs/2205.09037