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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
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
Extensions of compressed sensing
Signal Processing, 2006Yaakov Tsaig, David L. Donoho
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An effective image encryption algorithm based on compressive sensing and 2D-SLIM
Optics and Lasers in Engineering, 2020Kehui Sun, Shaobo He, Congxu Zhu
exaly
Measure What Should be Measured: Progress and Challenges in Compressive Sensing
IEEE Signal Processing Letters, 2012Thomas Strohmer
exaly
Embedding cryptographic features in compressive sensing
Neurocomputing, 2016Yushu Zhang, Jiantao Zhou, Fei Chen
exaly
Compressive Sensing by Random Convolution
SIAM Journal on Imaging Sciences, 2009Justin Romberg
exaly