Explorando a eficiência de compressão e qualidade de vídeo: um estudo sobre Codecs de vídeo baseados em Deep Learning
Advancements in video streaming technology have revolutionized the way content Multimedia is consumed, becoming an essential component in the distribution of information and entertainment. Transmission efficiency and video quality are only critical aspects, especially in a scenario where the demand...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Federal de Sergipe (UFS) |
| Repositorio: | Repositório Institucional da UFS |
| Idioma: | portugués |
| OAI Identifier: | oai:oai:ri.ufs.br:repo_01:riufs/22466 |
| Acceso en línea: | https://ri.ufs.br/jspui/handle/riufs/22466 |
| Access Level: | acceso abierto |
| Palabra clave: | Codificador e Decodificador (CODEC) Deep Learning Compressão de vídeo Streaming Vídeo Compression |
| Sumario: | Advancements in video streaming technology have revolutionized the way content Multimedia is consumed, becoming an essential component in the distribution of information and entertainment. Transmission efficiency and video quality are only critical aspects, especially in a scenario where the demand for high-resolution content is constant growth To meet these needs, video encoders/decoders (Codecs) and Efficient compression techniques are essential. Traditionally, Codecs like H.264 and H.265 played a key role in video compression, but it was also learned profound brought new possibilities and challenges to this field. This work aimed to investigate and compare innovative solutions that can be applied to improve efficiency compression and video quality in real-time streaming scenarios using or potential of deep learning techniques. The study included analysis of publications identify the proposed contributions and their limitations within the paradigm Codec based on Deep Learning, in relation to traditional approaches to optimization CODECs with the aim of reducing the amount of bandwidth used. |
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