Results 81 to 90 of about 5,989,108 (296)
Научно-технический вестник информационных технологий, механики и оптикиModern technologies for the development and operation of neural networks are vulnerable to computer attacks with the introduction of software backdoors. Program backdoors can remain hidden indefinitely until activated by input of modified data containing
A. B. Menisov +2 more
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Analog computation via neural networks
[1993] The 2nd Israel Symposium on Theory and Computing Systems, 1994 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hava T. Siegelmann, Eduardo D. Sontag
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FEBS Letters, EarlyView.CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source
Computational Capabilities of Graph Neural Networks
IEEE Transactions on Neural Networks, 2009 In this paper, we will consider the approximation properties of a recently introduced neural network model called graph neural network (GNN), which can be used to process-structured data inputs, e.g., acyclic graphs, cyclic graphs, and directed or undirected graphs.
SCARSELLI F. +4 more
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Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential
FEBS Letters, EarlyView.Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta +3 more
wiley +1 more source
Object Detection: Training From Scratch
IEEE Access, 2020 The development of deep neural networks has driven the development of computer vision. Deep neural networks play an important role in object detection. To improve network performance, before using neural networks for object detection, they are commonly ...
Kai Zhao, Yan Zhou, Xin Chen
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Epigenetic reprogramming of lineage switching in cancer
FEBS Letters, EarlyView.Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı +4 more
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Artificial neural networks and computer image analysis in the evaluation of selected quality parameters of pea seeds [PDF]
E3S Web of Conferences, 2019 The aim of the study was to develop an innovative method of modelling the process of evaluating the quality of agricultural crops on the basis of computer image analysis and artificial neural networks (ANN).
Szwedziak Katarzyna
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Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Generative capacities of cellular automata codification for evolution of NN codification [PDF]
, 2002 Proceeding of: International Conference on Artificial Neural Networks. ICANN 2002, Madrid, Spain, August 28-30, 2002Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary
Gutiérrez Sánchez, Germán +3 more
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