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Applying textural Law’s masks to images using machine learning
(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 ...
Deep learning based static hand gesture recognition
(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 ...
Generating images using generative adversarial networks based on text descriptions
(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 ...
Human-machine interactions based on hand gesture recognition using deep learning methods
(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 ...
Noisy image enhancements using deep learning techniques
(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, ...
Detection of heart pathology using deep learning methods
(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 ...
Fire detection using deep learning methods
(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 ...
Human-machine interactions based on hand gesture recognition using deep learning methods
(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 ...
Fire detection using deep learning methods
(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. ...
Deep learning based static hand gesture recognition
(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 ...










