Results 261 to 270 of about 630,255 (299)
Some of the next articles are maybe not open access.
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
Using compression codes in compressed sensing
2016 IEEE Information Theory Workshop (ITW), 2016Data compression and compressed sensing algorithms exploit the structure present in a signal for its efficient representation and measurement, respectively. While most state-of-the-art data compression codes take advantage of complex patterns present in signals of interest, this is not the case in compressed sensing.
Farideh Ebrahim Rezagah +3 more
openaire +1 more source
Physics and Chemistry of the Earth, 1968
Methods for the determination of the density of liquids can be divided into three classes as follows. 1. Methods in which the density is measured in terms of the fundamental physical standards of measurement. 2. Methods in which it is measured relative to the density of a reference liquid or solid.
openaire +1 more source
Methods for the determination of the density of liquids can be divided into three classes as follows. 1. Methods in which the density is measured in terms of the fundamental physical standards of measurement. 2. Methods in which it is measured relative to the density of a reference liquid or solid.
openaire +1 more source
Reweighted Compressive Sampling for image compression
2009 Picture Coding Symposium, 2009Compressive Sampling (CS), is an emerging theory which points us a promising direction of designing novel efficient data compression techniques. However, the conventional CS adopts a non-discriminated sampling scheme which usually gives poor performance on realistic complex signals.
Yi Yang 0041 +4 more
openaire +1 more source
Compressible turbulent mixing: Effects of compressibility
Physical Review E, 2016We studied by numerical simulations the effects of compressibility on passive scalar transport in stationary compressible turbulence. The turbulent Mach number varied from zero to unity. The difference in driven forcing was the magnitude ratio of compressive to solenoidal modes.
openaire +2 more sources
A new compression method for compressed matching
Proceedings DCC 2000. Data Compression Conference, 2002A practical adaptive compression algorithm based on LZSS is presented, which is especially constructed to solve the compressed pattern matching problem, i.e., pattern matching directly in a compressed text without decompressing.
Shmuel T. Klein, Dana Shapira
openaire +1 more source