Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
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Applying textural Law’s masks to images using machine learning 

Abdikerimova, Gulzira; Yessenova, Moldir; Yerzhanova, Akbota; Manbetova, Zhanat; Murzabekova, Gulden; Kaibassova, Dinara; Bekbayeva, Roza; Aldashova, Madina (International Journal of Electrical and Computer Engineering, 2023)
Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the increase in the computing power of modern computers and the emergence of very large training data sets available in global networks. The article considers Laws texture masks as weights for a machinelearning algorithm for clustering aerospace images. The use of Laws texture masks ...
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Deep learning based static hand gesture recognition 

Satybaldina, Dina; Kalymova, Gulzia (Indonesian Journal of Electrical Engineering and Computer Science, 2021)
Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet ...
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Generating images using generative adversarial networks based on text descriptions 

Turarova, Marzhan; Bekbayeva, Roza; Abdykerimova, Lazzat; Aitimov, Murat; Bayegizova, Aigulim; Smailova, Ulmeken; Kassenova, Leila; Glazyrina, Natalya (International Journal of Electrical and Computer Engineering, 2024)
Modern developments in the fields of natural language processing (NLP) and computer vision (CV) emphasize the increasing importance of generating images from text descriptions. The presented article analyzes and compares two key methods in this area: generative adversarial network with conditional latent semantic analysis (GAN-CLS) and ultra-long transformer network ...
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Human-machine interactions based on hand gesture recognition using deep learning methods 

Zholshiyeva, Lazzat; Manbetova, Zhanat; Kaibassova, Dinara; Kassymova, Akmaral; Tashenova, Zhuldyz; Baizhumanov, Saduakas; Yerzhanova, Akbota; Aikhynbay, Kulaisha (International Journal of Electrical and Computer Engineering, 2024)
Human interaction with computers and other machines is becoming an increasingly important and relevant topic in the modern world. Hand gesture recognition technology is an innovative approach to managing computers and electronic devices that allows users to interact with technology through gestures and hand movements. This article presents deep learning methods that ...
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Noisy image enhancements using deep learning techniques 

Daurenbekov, Kuanysh; Aitimova, Ulzada; Dauitbayeva, Aigul; Sankibayev, Arman; Tulegenova, Elmira; Yerzhan, Assel; Yerzhanova, Akbota; Mukhamedrakhimova, Galiya (International Journal of Electrical and Computer Engineering, 2024)
This article explores the application of deep learning techniques to improve the accuracy of feature enhancements in noisy images. A multitasking convolutional neural network (CNN) learning model architecture has been proposed that is trained on a large set of annotated images. Various techniques have been used to process noisy images, including the use of data augmentation, ...
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Detection of heart pathology using deep learning methods 

Naizagarayeva, Akgul; Abdikerimova, Gulzira; Shaikhanova, Aigul; Glazyrina, Natalya; Bekmagambetova, Gulmira; Mutovina, Natalya; Yerzhan, Assel; Tanirbergenov, Adilbek (International Journal of Electrical and Computer Engineering, 2023)
In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows ...
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Fire detection using deep learning methods 

Bayegizova, Aigulim; Abdikerimova, Gulzira; Kaliyeva, Samal; Shaikhanova, Aigul; Shangytbayeva, Gulmira; Sugurova, Laura; Sugur, Zharkynay; Saimanova, Zagira (International Journal of Electrical and Computer Engineering, 2024)
Fire detection is an important task in the field of safety and emergency prevention. In recent years, deep learning methods have shown high efficiency in solving various computer vision problems, including detecting objects in images. In this paper, monitoring wildfires was considered, which allows you to quickly respond to them and prevent their spread using deep learning ...
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Human-machine interactions based on hand gesture recognition using deep learning methods 

Zholshiyeva, Lazzat; Manbetova, Zhanat; Kaibassova, Dinara; Kassymova, Akmaral; Tashenova, Zhuldyz; Baizhumanov, Saduakas; Yerzhanova, Akbota; Aikhynbay, Kulaisha (International Journal of Electrical and Computer Engineering, 2024)
Human interaction with computers and other machines is becoming an increasingly important and relevant topic in the modern world. Hand gesture recognition technology is an innovative approach to managing computers and electronic devices that allows users to interact with technology through gestures and hand movements. This article presents deep learning methods that allow ...
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Fire detection using deep learning methods 

Bayegizova, Aigulim; Abdikerimova, Gulzira; Kaliyeva, Samal; Shaikhanova, Aigul; Shangytbayeva, Gulmira; Sugurova, Laura; Sugur, Zharkynay; Saimanova, Zagira (International Journal of Electrical and Computer Engineering, 2024)
Fire detection is an important task in the field of safety and emergency prevention. In recent years, deep learning methods have shown high efficiency in solving various computer vision problems, including detecting objects in images. In this paper, monitoring wildfires was considered, which allows you to quickly respond to them and prevent their spread using deep learning methods. ...
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Deep learning based static hand gesture recognition 

Satybaldina, Dina; Kalymova, Gulzia (Indonesian Journal of Electrical Engineering and Computer Science, 2021)
Hand gesture recognition becomes a popular topic of deep learning and provides many application fields for bridging the human-computer barrier and has a positive impact on our daily life. The primary idea of our project is a static gesture acquisition from depth camera and to process the input images to train the deep convolutional neural network pre-trained on ImageNet ...
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AuthorBayegizova, Aigulim (10)Yerzhanova, Akbota (10)Abdikerimova, Gulzira (8)Aitimov, Murat (8)Glazyrina, Natalya (7)Sankibayev, Arman (7)Bekbayeva, Roza (6)Kaibassova, Dinara (6)Manbetova, Zhanat (6)Mukhamedrakhimova, Galiya (6)... View MoreSubject
Machine learning (48)
Deep learning (19)Image processing (10)Computer vision (7)Classification (6)Clustering (6)Noisy image (6)Convolutional neural network (5)Blockchain (4)Discriminator (4)... View MoreDate Issued2024 (32)2023 (8)2025 (4)2021 (3)2022 (1)Has File(s)true (48)

Евразийский национальный университет имени Л.Н. Гумилева | Научная библиотека | Contact Us
Яндекс.Метрика
Научная библиотека | Contact Us