Results 251 to 260 of about 187,054 (294)
Some of the next articles are maybe not open access.
Compressive Sampling and Lossy Compression
IEEE Signal Processing Magazine, 2008Recent results in compressive sampling have shown that sparse signals can be recovered from a small number of random measurements. This property raises the question of whether random measurements can provide an efficient representation of sparse signals in an information-theoretic sense.
Vivek K. Goyal +2 more
openaire +1 more source
SIAM Journal on Computing, 1985
A notion of language compressibility is defined and it is proved that in a sufficiently sparse and ``easy''-computable language essentially all strings can be compressed efficiently. Similar results hold for a type of optimal compression (ranking). Examples of languages that cannot be compressed/ranked efficiently are also presented, as well as some ...
Andrew V. Goldberg, Michael Sipser
openaire +2 more sources
A notion of language compressibility is defined and it is proved that in a sufficiently sparse and ``easy''-computable language essentially all strings can be compressed efficiently. Similar results hold for a type of optimal compression (ranking). Examples of languages that cannot be compressed/ranked efficiently are also presented, as well as some ...
Andrew V. Goldberg, Michael Sipser
openaire +2 more sources
High compression ratio image compression
1993 IEEE International Symposium on Circuits and Systems, 2002An image compression method is proposed. It makes use of the wavelet transform (WT) with better frequency localization and the adaptive hierarchical vector quantization (AHVQ) technique. The WT provides a multifrequency channel representation for the image from which proper coding methods can be drawn.
Sheng Zhong, Qing-Yun Shi, Min-Teh Cheng
openaire +1 more source
Proceedings of the 3rd international conference on Computer graphics, virtual reality, visualisation and interaction in Africa, 2004
The great advances in the field of 3D scanning technologies have enabled the creation of meshes with hundred millions of polygons. Rendering data sets of that size is time consuming even with commodity graphics hardware. The QSplat technique that has been introduced by S. Rusinkiewics and M.
Namane, Rachid +2 more
openaire +2 more sources
The great advances in the field of 3D scanning technologies have enabled the creation of meshes with hundred millions of polygons. Rendering data sets of that size is time consuming even with commodity graphics hardware. The QSplat technique that has been introduced by S. Rusinkiewics and M.
Namane, Rachid +2 more
openaire +2 more sources
Journal of Chemical Information and Modeling, 2006
We present a simple and effective method for similarity searching in virtual high-throughput screening, requiring only a string-based representation of the molecules (e.g., SMILES) and standard compression software, available on all modern desktop computers.
James L. Melville +2 more
openaire +2 more sources
We present a simple and effective method for similarity searching in virtual high-throughput screening, requiring only a string-based representation of the molecules (e.g., SMILES) and standard compression software, available on all modern desktop computers.
James L. Melville +2 more
openaire +2 more sources
Near-Optimal Compression for Compressed Sensing
2015 Data Compression Conference, 2015In this note we study the under-addressed quantization stage implicit in any compressed sensing signal acquisition paradigm. We also study the problem of compressing the bit-stream resulting from the quantization. We propose using Sigma-Delta (a#x03A3;a#x0394;) quantization followed by a compression stage comprised of a discrete Johnson-Linden Strauss ...
Rayan Saab +2 more
openaire +1 more source
Spatiotemporal compressed sensing for video compression
2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017We present a hardware-friendly spatiotemporal compressed sensing framework for video compression. The spatiotemporal compressed sensing incorporates random sampling in both spatial and temporal domain to encode the video scene into a single coded image. During decoding, the video is reconstructed using dictionary learning and sparse recovery.
Tao Xiong +6 more
openaire +1 more source
Compressing YOLO Network by Compressive Sensing
2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017Object detection is one of the fundamental challenges in pattern recognition community. Recently, convolutional neural networks (CNN) are increasingly exploited in object detection, showing their promising potentials of generatively discovering patterns from quantity of labeled images.
Yirui Wu +3 more
openaire +1 more source
Lossless compression of already compressed textures
Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics, 2011Texture compression helps rendering by reducing the footprint in graphics memory, thus allowing for more textures, and by lowering the number of memory accesses between the graphics processor and memory, increasing performance and lowering power consumption.
Jacob Ström, Per Wennersten
openaire +1 more source
Compressive sensing for space image compressing
Proceedings of the 2016 International Conference on Intelligent Information Processing, 2016Compressive sensing is a new technique by which sparse signals are sampled and recovered from a few measurements. To address the disadvantages of traditional space image compressing methods, a complete new compressing scheme under the compressive sensing framework was developed in this paper.
Zheng Li +3 more
openaire +2 more sources