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Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images
VG Krasilenko, AA Lazarev… - … on Applications of …, 2017 - spiedigitallibrary.org
Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-
decoding and image clustering are discussed. The SLECNS architectures and their spatially …
decoding and image clustering are discussed. The SLECNS architectures and their spatially …
Design and simulation of optoelectronic neuron equivalentors as hardware accelerators of self-learning equivalent convolutional neural structures (SLECNS)
VG Krasilenko, AA Lazarev… - Neuro-inspired Photonic …, 2018 - spiedigitallibrary.org
In the paper, we consider the urgent need to create highly efficient hardware accelerators for
machine learning algorithms, including convolutional and deep neural networks (CNN and …
machine learning algorithms, including convolutional and deep neural networks (CNN and …
Using a multi-port architecture of neural-net associative memory based on the equivalency paradigm for parallel cluster image analysis and self-learning
VG Krasilenko, AA Lazarev… - Intelligent Robots …, 2013 - spiedigitallibrary.org
We consider equivalency models, including matrix-matrix and matrix-tensor and with the
dual adaptive-weighted correlation, multi-port neural-net auto-associative and hetero …
dual adaptive-weighted correlation, multi-port neural-net auto-associative and hetero …
Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering …
VG Krasilenko, AA Lazarev… - MIPPR 2017: Pattern …, 2018 - spiedigitallibrary.org
The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer
neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will …
neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will …
Experimental research of methods for clustering and selecting image fragments using spatial invariant equivalent models
VG Krasilenko, AA Lazarev… - … on Applications of …, 2014 - spiedigitallibrary.org
In the paper, we show that the nonlinear spatial non-linear equivalency functions on the
basis of continuous logic equivalence (nonequivalence) operations have better …
basis of continuous logic equivalence (nonequivalence) operations have better …
Using LabView for real-time monitoring and tracking of multiple biological objects
AI Nikolskyy, VG Krasilenko… - Health Monitoring of …, 2017 - spiedigitallibrary.org
Today real-time studying and tracking of movement dynamics of various biological objects is
important and widely researched. Features of objects, conditions of their visualization and …
important and widely researched. Features of objects, conditions of their visualization and …
[PDF][PDF] Експериментальні дослідження просторово-інваріантних еквівалентністних моделей асоціативної та гетероасоціативної пам'яті 2D образів
ВГ Красиленко, ДВ Нікітович - Системи обробки інформації, 2014 - irbis-nbuv.gov.ua
При моделюванні нейрофізіологічних процесів широко використовуються відповідні
моделі штучних нейронних мереж (ШНМ) та асоціативної пам'яті (АП). Теоретичною …
моделі штучних нейронних мереж (ШНМ) та асоціативної пам'яті (АП). Теоретичною …
[PDF][PDF] Simulation of self-learning clustering methods for selecting and grouping similar patches, using twodimensional nonlinear space-invariant models and functions …
VG Krasilenko, DV Nikitovich - Electronics and information …, 2016 - ir.lib.vntu.edu.ua
The results of modeling combined with self-training clustering method of image fragments.
For isolation, selection and use of cluster grouping of fragments of structural and topological …
For isolation, selection and use of cluster grouping of fragments of structural and topological …
Design and simulation of neuron-equivalentors array for creation of self-learning equivalent-convolutional neural structures (slecns)
V Krasilenko, N Yurchuk… - … університету.№ 3: 58-70., 2021 - ir.lib.vntu.edu.ua
In the paper, we consider the urgent need to create highly efficient hardware accelerators for
machine learning algorithms, including convolutional and deep neural networks (CNN and …
machine learning algorithms, including convolutional and deep neural networks (CNN and …