Artificial Intelligence for Multimedia Signal Processing
Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three ye...
Format: | eBook |
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Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
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Subjects: | |
Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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003 | oapen | ||
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006 | m o d | ||
007 | cr|mn|---annan | ||
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020 | |a 9783036549651 | ||
020 | |a 9783036549668 | ||
020 | |a books978-3-0365-4966-8 | ||
024 | 7 | |a 10.3390/books978-3-0365-4966-8 |2 doi | |
040 | |a oapen |c oapen | ||
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a TBX |2 bicssc | |
720 | 1 | |a Kim, Byung-Gyu |4 edt | |
720 | 1 | |a Jun, Dongsan |4 edt | |
720 | 1 | |a Jun, Dongsan |4 oth | |
720 | 1 | |a Kim, Byung-Gyu |4 oth | |
245 | 0 | 0 | |a Artificial Intelligence for Multimedia Signal Processing |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2022 | ||
300 | |a 1 online resource (212 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |f Unrestricted online access |2 star | |
520 | |a Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |u https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a History of engineering and technology |2 bicssc | |
653 | |a artificial intelligence | ||
653 | |a avatar | ||
653 | |a canonical correlation analysis (CCA) | ||
653 | |a channel attention networks | ||
653 | |a computer vision | ||
653 | |a content based recommend systems | ||
653 | |a content curation social networks | ||
653 | |a context-free grammar | ||
653 | |a convolutional neural network | ||
653 | |a convolutional neural network (CNN) | ||
653 | |a convolutional neural networks | ||
653 | |a data augmentation | ||
653 | |a deep learning | ||
653 | |a deep neural network | ||
653 | |a dense networks | ||
653 | |a depth 3D conversion | ||
653 | |a depth video | ||
653 | |a different recommend tasks | ||
653 | |a environmental sound recognition | ||
653 | |a feature combination | ||
653 | |a fluency evaluation | ||
653 | |a generative adversarial network | ||
653 | |a generative adversarial networks | ||
653 | |a graph convolutional networks | ||
653 | |a heartbeat classification | ||
653 | |a human-height estimation | ||
653 | |a image de-raining | ||
653 | |a image enhancement | ||
653 | |a image processing | ||
653 | |a image restoration | ||
653 | |a Indian Sign Language (ISL) | ||
653 | |a lightweight neural network | ||
653 | |a logical story unit detection (LSU) | ||
653 | |a multimodal joint representation | ||
653 | |a n/a | ||
653 | |a natural language processing | ||
653 | |a object detection | ||
653 | |a object re-ID | ||
653 | |a relativistic GAN | ||
653 | |a residual dense networks | ||
653 | |a residual networks | ||
653 | |a scene/place classification | ||
653 | |a semantic segmentation | ||
653 | |a sentiment classification | ||
653 | |a sign movement | ||
653 | |a single image artifacts reduction | ||
653 | |a single image super-resolution | ||
653 | |a speech conversion | ||
653 | |a speech enhancement | ||
653 | |a speech recognition | ||
653 | |a traffic surveillance image processing | ||
653 | |a variational autoencoder | ||
653 | |a visual sentiment analysis | ||
653 | |a weighting matrix | ||
793 | 0 | |a DOAB Library. | |
856 | 4 | 0 | |u https://directory.doabooks.org/handle/20.500.12854/97452 |7 0 |z Open Access: DOAB: description of the publication |
856 | 4 | 0 | |u https://mdpi.com/books/pdfview/book/5922 |7 0 |z Open Access: DOAB, download the publication |