Zobrazeno 1 - 8
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pro vyhledávání: '"Amigo, Glauco"'
Biased datasets are ubiquitous and present a challenge for machine learning. For a number of categories on a dataset that are equally important but some are sparse and others are common, the learning algorithms will favor the ones with more presence.
Externí odkaz:
http://arxiv.org/abs/2312.15307
The outcome of all time series cannot be forecast, e.g. the flipping of a fair coin. Others, like the repeated {01} sequence {010101...} can be forecast exactly. Algorithmic information theory can provide a measure of forecastability that lies betwee
Externí odkaz:
http://arxiv.org/abs/2304.10752
The identification of out-of-distribution data is vital to the deployment of classification networks. For example, a generic neural network that has been trained to differentiate between images of dogs and cats can only classify an input as either a
Externí odkaz:
http://arxiv.org/abs/2109.06168
The identification of out-of-distribution content is critical to the successful implementation of neural networks. Watchdog techniques have been developed to support the detection of these inputs, but the performance can be limited by the amount of a
Externí odkaz:
http://arxiv.org/abs/2108.09375
Publikováno v:
2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC).
The identification of out-of-distribution data is vital to the deployment of classification networks. For example, a generic neural network that has been trained to differentiate between images of dogs and cats can only classify an input as either a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47daa32418528cf732356bd511daaf7d
https://doi.org/10.1109/ccwc57344.2023.10099329
https://doi.org/10.1109/ccwc57344.2023.10099329
The capabilities of machine intelligence are bounded by the potential of data from the past to forecast the future. Deep learning tools are used to find structures in the available data to make predictions about the future. Such structures have to be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a0cad788f184b696c560b2029555080
Akademický článek
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Publikováno v:
Signal, Image & Video Processing; Jun2023, Vol. 17 Issue 4, p1535-1542, 8p