V. (pp. 437-442).Shafrir, U. 1995 . “Computer-based testing of reflective thinking: executive control of erroneous performance in 9 to 12 year old children.”. In Symbiosis of Human and Artefact Edited by: Anzai, Y., Ogawa, K. and Mori, H. Elsevier Sciences B.. (V.; New York...
2016 International Multidisciplinary Conference on Computer and Energy Science (SpliTech) 1–6. https://doi.org/10.1109/SpliTech.2016.7555926 McLaughlin M, Castro D (2020) The critics were wrong: NIST data shows the best facial recognition algorithms are neither racist nor sexist. ITIF, https:/...
However, even with state-of-the-art image segmentation algorithms, we can still see a large number of pixels with wrong labels in regions with indistinct RGB information, at object boundaries and in small-scale objects. We call these erroneous pixels. While hard-mining methods exist that train...
Table 9 shows the performance results of different algorithms for the S. aureus testing dataset (200,000 reads). All machine learning models (SVM, RF, LR, NB, and XGBoost) show excellent performance on the S. aureus dataset with a k-mer size of 15, achieving S ami et al. BMC...
When all focus pedigrees are analyzed in the first iteration, using HMM algorithms, the state sequence will only be uniquely defined in those regions where markers are fully informative. We then iteratively refine parameters to infer a consistent haplotype resolution in all markers step by step, no...
Yang, Z., Algesheimer, R., Tessone, C.: A comparative analysis of community detection algorithms on artificial networks. Sci. Rep. This work was partially conducted within the MaestroGraph project (612.001.553), funded by the Netherlands Organization for Scientific Research (NWO), and was parti...
The algorithm shows approximately 98.5% reliability as compared with the other existing algorithms due to its spatial-temporal features based on deep neural network architecture. Keywords: IoT node; spatial-temporal correlation; data reliability; hierarchical LSTM; data recovery; missing data; and ...
The algorithm shows approximately 98.5% reliability as compared with the other existing algorithms due to its spatial-temporal features based on deep neural network architecture. Keywords: IoT node; spatial-temporal correlation; data reliability; hierarchical LSTM; data recovery; missing data; and ...