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Video-Based Recognition of Human Activity Using Novel Feature Extraction Techniques
(MDPI, 2023-06-05)
This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature ...
Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images
(IEEE, 2023)
Recognition of continuous sign language is challenging as the number of words is a sentence and their boundaries are unknown during the recognition stage. This work proposes a two-stage solution in which the number of words ...
Decision-level fusion for single-view gait recognition with various carrying and clothing conditions
(Elsevier, 2017)
Gait Recognition is one of the latest and attractive biometric techniques, due to its potential in identification of individuals at a distance, unobtrusively and even using low resolution images. In this paper we focus on ...
IoT Based Smart City Bus Stops
(MDPI, 2019)
The advent of smart sensors, single system-on-chip computing devices, Internet of Things (IoT), and cloud computing is facilitating the design and development of smart devices and services. These include smart meters, smart ...
Static Video Summarization Using Video Coding Features with Frame-level Temporal Sub-Sampling and Deep Learning
(MDPI, 2023)
There is an abundance of digital video content due to the cloud’s phenomenal growth and security footage, it is therefore essential to summarize these videos in data centers. This paper offers innovative approaches to the ...
H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling
(IEEE, 2014)
The new video coding standard, HEVC, was developed to succeed the current standard, H.264/AVC, as the state of the art in video compression. However, there is a lot of legacy content encoded with H.264/AVC. This paper ...
FPGA-Based Network Traffic Classification Using Machine Learning
(IEEE Xplore, 2020)
Real-time classification of internet traffic is critical for the efficient management of networks. Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. ...
Predicting split decisions of coding units in HEVC video compression using machine learning techniques
(Springer, 2018)
In this work, we propose to reduce the complexity of HEVC video encoding by predicting the split decisions of coding units. We use a sequencedependent approach in which a number of frames belonging to the video being encoded ...
Continuous Arabic Sign Language Recognition in User Dependent Mode
(Scientific Research, 2010)
Arabic Sign Language recognition is an emerging field of research. Previous attempts at automatic visionbased recognition of Arabic Sign Language mainly focused on finger spelling and recognizing isolated gestures. In this ...
Altering Split Decisions of Coding Units for Message Embedding in HEVC
(Springer, 2017-05)
This paper proposes a novel message embedding solution based on modifying the split decisions of HEVC videos. The encoder starts by computing a mapping between the split decisions of a Coding Unit (CU) and its features ...