Simple architecture of convolution neural network for handwritten digit recognition

Simple architecture of convolution neural network for handwritten digit recognition

Gespeichert in:

Bibliographische Detailangaben
Datum:	2013
1. Verfasser:	V. V. Lukovich
Format:	Artikel
Sprache:	English
Veröffentlicht:	2013
Schriftenreihe:	Cybernetics and computer engineering
Online Zugang:	http://jnas.nbuv.gov.ua/article/UJRN-0000035057
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:	Library portal of National Academy of Sciences of Ukraine \| LibNAS

Institution

Library portal of National Academy of Sciences of Ukraine | LibNAS

Ähnliche Einträge

Comparative Analysis of the Application of Multilayer and Convolutional Neural Networks for Recognition of Handwritten Letters of the Azerbaijani Alphabet
von: Mustafayev, E., et al.
Veröffentlicht: (2021)

Comparative Analysis of the Application of Multilayer and Convolutional Neural Networks for Recognition of Handwritten Letters of the Azerbaijani Alphabet
von: E. Mustafayev, et al.
Veröffentlicht: (2021)

Ukrainian dactyl alphabet gesture recognition using convolutional neural networks with 3D convolutions
von: S. S. Kondratiuk
Veröffentlicht: (2019)

A model of a convolutional neural network and software for typical insect pests recognition
von: Bezliudnyi, Y.S., et al.
Veröffentlicht: (2021)

Development and research of a modified convolutional neural network for malaria cell pattern recognition
von: Федорченко, Є. М., et al.
Veröffentlicht: (2023)

Improving face recognition models using convolutional neural networks, metric learning and optimization methods
von: A. M. Litvynchuk, et al.
Veröffentlicht: (2021)

Ukrainian dactyl alphabet gesture recognition using cross platform software and convolutional neural networks
von: S. S. Kondratiuk
Veröffentlicht: (2019)

An example of the application of neural networks of a simple architecture to unfocused well electrometry probes
von: Myrontsov, Mykyta L.
Veröffentlicht: (2024)

Intelligent recognition and integration of graphical elements into virtual surrounding within augmented reality using hybrid convolutional neural networks
von: V. Sineglazov, et al.
Veröffentlicht: (2023)

Using convolutional neural networks for breast cancer diagnosing
von: M. Naderan, et al.
Veröffentlicht: (2019)

Neural Network Technologies in the Problem of Handwriting Recognition
von: A. D. Goltsev, et al.
Veröffentlicht: (2018)

Analyzing the models of speech recognition on the basis of neural networks of deep learning for examination of digital phonograms
von: V. I. Solovev, et al.
Veröffentlicht: (2021)

Convolutional neural network model and software for classification of typical pests
von: Bezliudnyi, Y.S., et al.
Veröffentlicht: (2022)

Neural network modeling of graphic recognition processes
von: Ye. M. Chichirin, et al.
Veröffentlicht: (2019)

Recognition of Handwritten Texts on Images Using Deep Machine Learning
von: M. D. Snitko, et al.
Veröffentlicht: (2024)

Histological and cytological images classification based on convolutional neural networks
von: O. M. Berezkyi, et al.
Veröffentlicht: (2017)

Information technology for the early diagnosys of pneumonia using convolutional neural networks
von: P. M. Radjuk, et al.
Veröffentlicht: (2021)

Using an ensemble of convolutional neural networks to process remote sensing data
von: E. E. Marushko, et al.
Veröffentlicht: (2018)

Convolutional neural networks in tasks of agricultural vegetation state monitoring on aerial images
von: V. V. Ganchenko, et al.
Veröffentlicht: (2018)

A prediction of the frequency of non-periodic signals based on convolutional neural networks
von: S. O. Subbotin, et al.
Veröffentlicht: (2018)

A prediction of the frequency of non-periodic signals based on convolutional neural networks
von: Subbotin, S. A., et al.
Veröffentlicht: (2018)

Architectural and mathematical fundamentals of improvement neural networks for classification of images
von: V. I. Sliusar
Veröffentlicht: (2022)

Convolutional Neural Networks for Determining the Ion Beam Impact on a Space Debris Object
von: M. O. Redka, et al.
Veröffentlicht: (2023)

Developing a semantic image model using machine learning based on convolutional neural networks
von: P. I. Andon, et al.
Veröffentlicht: (2020)

Developing a semantic image model using machine learning based on convolutional neural networks
von: Andon, P.I., et al.
Veröffentlicht: (2020)

Analysis of remote sensing images by methods of convolutional neural networks and marked random point fields
von: Ya. Kosarevych, et al.
Veröffentlicht: (2021)

Self-learning neural network technologies in the systems of structural recognition of visual objects
von: Berestovskii, A. E., et al.
Veröffentlicht: (2015)

Criteria for Comparison of Recognition Models Based on Neural Networks and Analysis of Their Mutual Relations
von: S. A. Subbotin
Veröffentlicht: (2014)

A Simple Stuck-at-Faults Detection Method in Digital Artificsal Neurea Networks
von: B. Y. Rytsar
Veröffentlicht: (2023)

Analysis of satellite data time series for forest monitoring using neural networks based on three-dimensional convolutions
von: A. Shelestov, et al.
Veröffentlicht: (2024)

A generalized methodology of sign language recognition on video streams based on neural networks and transformers
von: Кузнєцова, Н. В., et al.
Veröffentlicht: (2023)

A Convolutional Neural Network Model and Software Tool for Classifying the Presence of a Medical Mask on a Human Face
von: Hryhorenko, Y.S., et al.
Veröffentlicht: (2023)

Simple and cheap photosystem for herbarium digitization
von: A. Novikov, et al.
Veröffentlicht: (2021)

Recognition and calculation of objects in images using YOLOv3 architecture
von: V. A. Hrabovskyi, et al.
Veröffentlicht: (2021)

Application of the volume learning algorithm artificial neural networks for recognition of the type of interaction between neurons from their cross-correlation histograms
von: Kovalishyn, V.V., et al.
Veröffentlicht: (2005)

Pysanka Painting of Podillia in Handwritten Heritage of 1920s
von: V. Tkachenko
Veröffentlicht: (2021)

Brain and Artificial Neural Networks
von: V. V. Storozh
Veröffentlicht: (2013)

Neural networks’ learning process acceleration
von: Katerynych, L., et al.
Veröffentlicht: (2020)

Application of neural networks in OLAP-systems
von: Nabibayeva, G.Ch.
Veröffentlicht: (2024)

Neural networks’ learning process acceleration
von: Katerynych, L., et al.
Veröffentlicht: (2020)