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Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding
(Springer, 2020)
This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding ...
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. ...
Enhanced Water Network Leak Detection Methods
(2021-04)
Water is an essential element and source of life. It is considered a scarce element that goes through several procedures for it be consumable. Once the water is treated and is deemed potable or clean, it is then distributed ...
Detecting Double and Triple Compression in HEVC Videos Using the Same Bit Rate
(Springer, 2021)
Digital video forensics refers to the process of analysing, examining, evaluating and comparing a video for use in legal matters. In digital video forensics, the main aim is to detect and identify video forgery to ensure ...
Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems
(2021-11)
The electronic nose, commonly known as the E-nose that combines gas sensor arrays (GSAs) with machine learning, has gained a strong foothold in gas sensing technology. The E-nose, inspired from the human olfactory system, ...
HEVC Video Encryption with High Capacity Message Embedding by Altering Picture Reference Indices and Motion Vectors
(IEEE, 2022)
A high capacity message embedding in encrypted HEVC video is proposed in this paper. The challenges addressed in this paper include keeping the encrypted video compliant with standardized decoders, correctly decrypting the ...
Data Embedding in Scrambled Video by Rotating Motion Vectors
(Springer, 2022-03)
Data embedding in videos has several important applications including Digital Rights Management, preserving confidentiality of content, authentication and tampering detection. This paper proposes a novel data embedding ...
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
(Sage Publishing, 2021)
Conventional damage detection techniques are gradually being replaced by state-of-the-art smart monitoring and decision-making solutions. Near real-time and online damage assessment in structural health monitoring (SHM) ...
Prediction of EV Charging Behavior Using Machine Learning
(IEEE Access, 2021)
As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are becoming increasingly popular for their contribution in reducing greenhouse gas emissions. One of the key challenges, however, ...
Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning
(2020-04)
Genuineness of smiles is one aspect of the field of deception recognition, one that is prevalent in myriad social situations, and it is not easy to tell when a person’s smile is genuine or not for the average person. Machine ...