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Fast Detection and Classification of Dangerous Urban Sounds Using Deep Learning
(Computers, Materials & Continua, 2023)
Video analytics is an integral part of surveillance cameras. Compared to video analytics, audio analytics offers several benefits, including
less expensive equipment and upkeep expenses. Additionally, the volume of
the audio datastream is substantially lower than the video camera datastream, especially concerning real-time operating systems, which makes it less
demanding of ...
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 ...
Analysis of the emotional coloring of text using machine and deep learning methods
(International Journal of Electrical and Computer Engineering, 2024)
The presented scientific article is a comprehensive study of machine learning
and deep learning methods in the context of emotion recognition in text data.
The main goal of the study is to conduct a comprehensive analysis and
comparison of various machine learning and deep learning methods to
classify emotions in text. During the work, special attention was paid to the ...
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, ...
Fast Detection and Classification of Dangerous Urban Sounds Using Deep Learning
(Computers, Materials & Continua, 2023)
Video analytics is an integral part of surveillance cameras. Compared to video analytics, audio analytics offers several benefits, including
less expensive equipment and upkeep expenses. Additionally, the volume of
the audio datastream is substantially lower than the video camera datastream, especially concerning real-time operating systems, which makes it less
demanding of ...
Application of deep learning methods for automated analysis of retinal structures in ophthalmology
(International Journal of Electrical and Computer Engineering, 2024)
This article examines a current area of research in the field of ophthalmology
the use of deep learning methods for automated analysis of retinal structures.
This work explores the use of deep learning methods such as EfficientNet
and DenseNet for the automated analysis of retinal structures in
ophthalmology. EfficientNet, originally proposed to balance between
accuracy and ...
Analysis of the emotional coloring of text using machine and deep learning methods
(International Journal of Electrical and Computer Engineering, 2024)
The presented scientific article is a comprehensive study of machine learning
and deep learning methods in the context of emotion recognition in text data.
The main goal of the study is to conduct a comprehensive analysis and
comparison of various machine learning and deep learning methods to
classify emotions in text. During the work, special attention was paid to the
analysis ...
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 ...
Automatic Classification of Scanned Electronic University Documents using Deep Neural Networks with Conv2D Layers
(International Journal of Advanced Computer Science and Applications, 2023)
This paper proposes a novel approach for scanned
document categorization using a deep neural network
architecture. The proposed approach leverages the strengths of
both convolutional neural networks (CNNs) and recurrent neural
networks (RNNs) to extract features from the scanned documents
and model the dependencies between words in the documents.
The pre-processed documents ...










