Results 221 to 230 of about 2,863,027 (299)
Some of the next articles are maybe not open access.
Entropy Coding and Entropy Coding Improvements of JPEG XS
2018 Data Compression Conference, 2018JPEG XS is a new standard for low-latency and low-complexity coding designed by the JPEG committee. Unlike former developments, optimal rate distortion performance is only a secondary goal; the focus of JPEG~XS is to enable cost-efficient, easy to parallelize implementations suitable for FPGAs or GPUs. In this article, we shed some light on the entropy
Thomas Richter +3 more
openaire +2 more sources
IEEE transactions on broadcasting, 2023
The worldwide commercialization of fifth generation (5G) wireless networks are pushing toward the deployment of immersive and high-quality VR-based telepresence systems. Among them, 3D object is generally digitized and represented as point cloud. However,
Pan Gao +3 more
semanticscholar +1 more source
The worldwide commercialization of fifth generation (5G) wireless networks are pushing toward the deployment of immersive and high-quality VR-based telepresence systems. Among them, 3D object is generally digitized and represented as point cloud. However,
Pan Gao +3 more
semanticscholar +1 more source
Entropy Coding-based Lossless Compression of Asynchronous Event Sequences
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023The event sensor acquires large amounts of data as events are triggered at microsecond time resolution. In this paper, a novel entropy coding-based method is proposed for encoding asynchronous event sequences. The proposed method employs the event coding
I. Schiopu, R. Bilcu
semanticscholar +1 more source
Pre-Training General Trajectory Embeddings With Maximum Multi-View Entropy Coding
IEEE Transactions on Knowledge and Data Engineering, 2022Spatio-temporal trajectories provide valuable information about movement and travel behavior, enabling various downstream tasks that in turn power real-world applications.
Yan Lin, Huaiyu Wan, S. Guo, Youfang Lin
semanticscholar +1 more source
Deep Autoencoder-based Massive MIMO CSI Feedback with Quantization and Entropy Coding
Global Communications Conference, 2021Techniques which leverage channel state information (CSI) at a transmitter to adapt wireless signals to changing propagation conditions have been shown to improve the reliability of modern multiple input multiple output (MIMO) communication systems.
Sriram Ravula, Swayambhoo Jain
semanticscholar +1 more source
Picture Coding Symposium, 2021
Recent works on learned image coding using autoencoder models have achieved promising results in rate-distortion performance. Typically, an autoencoder is used to transform an image into a latent tensor, which is then quantized and entropy coded.
Zhongzheng Yuan +4 more
semanticscholar +1 more source
Recent works on learned image coding using autoencoder models have achieved promising results in rate-distortion performance. Typically, an autoencoder is used to transform an image into a latent tensor, which is then quantized and entropy coded.
Zhongzheng Yuan +4 more
semanticscholar +1 more source
Adaptive Entropy-coded Subband Coding Of Images
Proceedings. 1991 IEEE International Symposium on Information Theory, 1992The authors describe a design approach, called 2-D entropy-constrained subband coding (ECSBC), based upon recently developed 2-D entropy-constrained vector quantization (ECVQ) schemes. The output indexes of the embedded quantizers are further compressed by use of noiseless entropy coding schemes, such as Huffman or arithmetic codes, resulting in ...
Y H, Kim, J W, Modestino
openaire +3 more sources
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding
Neural Information Processing Systems, 2020Variational Autoencoders (VAEs) have seen widespread use in learned image compression. They are used to learn expressive latent representations on which downstream compression methods can operate with high efficiency.
Gergely Flamich +2 more
semanticscholar +1 more source