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...
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| HerausgeberIn: | |
|---|---|
| Sonstige: | |
| Year of Publication: | 2022 |
| Language: | English |
| Physical Description: | 1 electronic resource (212 p.) |
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| 100 | 1 | |a Kim, Byung-Gyu |4 edt | |
| 245 | 1 | 0 | |a Artificial Intelligence for Multimedia Signal Processing |
| 260 | |a Basel |b MDPI Books |c 2022 | ||
| 300 | |a 1 electronic resource (212 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 506 | |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. | ||
| 546 | |a English | ||
| 650 | 7 | |a Technology: general issues |2 bicssc | |
| 650 | 7 | |a History of engineering & technology |2 bicssc | |
| 653 | |a human-height estimation | ||
| 653 | |a depth video | ||
| 653 | |a depth 3D conversion | ||
| 653 | |a artificial intelligence | ||
| 653 | |a convolutional neural networks | ||
| 653 | |a deep neural network | ||
| 653 | |a convolutional neural network | ||
| 653 | |a environmental sound recognition | ||
| 653 | |a feature combination | ||
| 653 | |a multimodal joint representation | ||
| 653 | |a content curation social networks | ||
| 653 | |a different recommend tasks | ||
| 653 | |a content based recommend systems | ||
| 653 | |a scene/place classification | ||
| 653 | |a semantic segmentation | ||
| 653 | |a deep learning | ||
| 653 | |a weighting matrix | ||
| 653 | |a speech enhancement | ||
| 653 | |a generative adversarial network | ||
| 653 | |a relativistic GAN | ||
| 653 | |a lightweight neural network | ||
| 653 | |a single image super-resolution | ||
| 653 | |a image enhancement | ||
| 653 | |a image restoration | ||
| 653 | |a residual dense networks | ||
| 653 | |a visual sentiment analysis | ||
| 653 | |a sentiment classification | ||
| 653 | |a graph convolutional networks | ||
| 653 | |a generative adversarial networks | ||
| 653 | |a traffic surveillance image processing | ||
| 653 | |a image de-raining | ||
| 653 | |a fluency evaluation | ||
| 653 | |a speech recognition | ||
| 653 | |a data augmentation | ||
| 653 | |a variational autoencoder | ||
| 653 | |a speech conversion | ||
| 653 | |a heartbeat classification | ||
| 653 | |a convolutional neural network (CNN) | ||
| 653 | |a canonical correlation analysis (CCA) | ||
| 653 | |a Indian Sign Language (ISL) | ||
| 653 | |a natural language processing | ||
| 653 | |a avatar | ||
| 653 | |a sign movement | ||
| 653 | |a context-free grammar | ||
| 653 | |a object detection | ||
| 653 | |a logical story unit detection (LSU) | ||
| 653 | |a object re-ID | ||
| 653 | |a computer vision | ||
| 653 | |a image processing | ||
| 653 | |a single image artifacts reduction | ||
| 653 | |a dense networks | ||
| 653 | |a residual networks | ||
| 653 | |a channel attention networks | ||
| 776 | |z 3-0365-4966-8 | ||
| 776 | |z 3-0365-4965-X | ||
| 700 | 1 | |a Jun, Dongsan |4 edt | |
| 700 | 1 | |a Kim, Byung-Gyu |4 oth | |
| 700 | 1 | |a Jun, Dongsan |4 oth | |
| 906 | |a BOOK | ||
| ADM | |b 2024-03-02 08:12:36 Europe/Vienna |f system |c marc21 |a 2022-09-22 08:09:39 Europe/Vienna |g false | ||
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