Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

• Other Authors: Kim, Cheonshik (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Technology: general issues; History of engineering & technology; data hiding; AMBTC; BTC; Hamming code; LSB; predicate encryption; inner product encryption; constant-size private key; efficient decryption; constant pairing computations; watermarking; self-embedding; digital signature; fragile watermarking; constrained backtracking matching pursuit; sparse reconstruction; compressed sensing; greedy pursuit algorithm; image processing; visual surveillance; deep learning; object detection; latency optimization; mobile edge cloud; connected autonomous cars; smart city; video surveillance; physical layer security; secure transmission; secrecy capacity; secrecy capacity optimization artificial noise; power allocation; channel estimation error; neural network; transfer learning; scalograms; MFCC; Log-mel; pre-trained models; seismic patch classification; CNN-features; data complexity; handwritten text recognition; Residual Network; Transformer model; named entity recognition; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

Summary

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read.

Physical Description

1 electronic resource (196 p.)

ISBN

books978-3-0365-5394-8
9783036553931
9783036553948

Access

Open Access