A review on federated learning towards image processing
Nowadays, data privacy is an important consideration in machine learning. This paper
provides an overview of how Federated Learning can be used to improve data security and …
provides an overview of how Federated Learning can be used to improve data security and …
A survey of human action recognition and posture prediction
Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …
the action and postures of persons in videos. They are both active research topics in …
Videollm: Modeling video sequence with large language models
With the exponential growth of video data, there is an urgent need for automated technology
to analyze and comprehend video content. However, existing video understanding models …
to analyze and comprehend video content. However, existing video understanding models …
A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection
In this article, we implement an action recognition technique based on features fusion and
best feature selection. In the proposed method, HSI color transformation is performed in the …
best feature selection. In the proposed method, HSI color transformation is performed in the …
Deep neural network features fusion and selection based on PLS regression with an application for crops diseases classification
Objective: The plants diseases affect both the production and quality of food in the
agriculture sector. Computer vision techniques can contribute significantly by detecting the …
agriculture sector. Computer vision techniques can contribute significantly by detecting the …
A resource conscious human action recognition framework using 26-layered deep convolutional neural network
Vision-based human action recognition (HAR) is a hot topic of research from the decade due
to a few popular applications such as visual surveillance and robotics. For correct action …
to a few popular applications such as visual surveillance and robotics. For correct action …
Hybrid malware classification method using segmentation-based fractal texture analysis and deep convolution neural network features
As the number of internet users increases so does the number of malicious attacks using
malware. The detection of malicious code is becoming critical, and the existing approaches …
malware. The detection of malicious code is becoming critical, and the existing approaches …
Human action recognition: a paradigm of best deep learning features selection and serial based extended fusion
Human action recognition (HAR) has gained significant attention recently as it can be
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …
StomachNet: Optimal deep learning features fusion for stomach abnormalities classification
A fully automated design is proposed in this work employing optimal deep learning features
for classifying gastrointestinal infections. Here, three prominent infections–ulcer, bleeding …
for classifying gastrointestinal infections. Here, three prominent infections–ulcer, bleeding …
A survey of video surveillance systems in smart city
Y Myagmar-Ochir, W Kim - Electronics, 2023 - mdpi.com
Smart cities are being developed worldwide with the use of technology to improve the
quality of life of citizens and enhance their safety. Video surveillance is a key component of …
quality of life of citizens and enhance their safety. Video surveillance is a key component of …