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Driver Drowsiness Detection using Machine Learning and Deep Learning Techniques: A Systematic Review. [PDF]
Arch Acad Emerg MedGhaffari Fam S +5 more
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Unsupervised Feature Learning Using Recurrent Neural Nets for Segmenting Hyperspectral Images
IEEE Geoscience and Remote Sensing Letters, 2021Although deep learning is gaining more widespread use in hyperspectral image analysis, it is challenging to train high-capacity models in a supervised way--ground-truth sets are expensive to obtain, and they are practically always extremely imbalanced.
Michal Kawulok +2 more
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A Structure Theory for Identification of Recurrent Neural Nets - Part 1
IFAC Postprint Volumes IPPV / International Federation of Automatic Control, 1998Abstract This paper extends some results on identifiability of recurrent (dynamic) neural nets obtained by F.Albertini and E.Sontag. A topological and geometrical description of the set of identifiable paranleters is given. In addition it is shown that the classes of observationally equivalent non-nlinimal systems are essentially finite unions of ...
Monika Dörfler, Manfred Deistler
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Recurrent neural nets as dynamical Boolean systems with application to associative memory
IEEE Transactions on Neural Networks, 1997Discrete-time/discrete-state recurrent neural networks are analyzed from a dynamical Boolean systems point of view in order to devise new analytic and design methods for the class of both single and multilayer recurrent artificial neural networks. With the proposed dynamical Boolean systems analysis, we are able to formulate necessary and sufficient ...
M H Hassoun
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Efficient Modeling of Contextual Mappings by Context-dependent Feedforward and Recurrent Neural Nets
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006The paper addresses the issue of solving real world problems by neural nets. The motivations for using contextual information in modeling complex dependencies between input data are discussed. The models of a context-dependent neuron and multi-layer perceptron are recalled along with a brief discussion on their properties and efficient training ...
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From chaos to clock in recurrent neural net. Case study
Biosystems, 2022What is the reason for complex dynamical patterns registered from real biological neuronal networks? Noise and dynamical reconfiguring of a network (functional/dynamic connectome) were proposed as possible answers. In this case study, we report a complex dynamical pattern observed in a simple deterministic network of 25 excitatory neurons with fixed ...
Alexander K. Vidybida, Olha Shchur
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