Results 281 to 290 of about 868,109 (319)
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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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.
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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
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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
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