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JPEG2000 (j2k) is a highly popular format for image and video compression.With the rapidly growing applications of cloud based image classification, most existing j2k-compatible schemes would stream compressed color images from the source before reconstruction at the processing center as inputs to deep CNNs.
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JPEG2000 Image Compression Fundamentals, Standards and Practice
D. Taubman and M. Marcellin, · 2012
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A. Levinskis, · 2013
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O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei, · 2015
Cited alongside, same era.
“Advanced image classification using wavelets and convolutional neural networks,”
T. Williams and R. Li, · 2016
Cited alongside, same era.
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D. Fu and G. Guimaraes, · 2016
Cited alongside, same era.
“Deep residual learning for image recognition,”
K. He, X. Zhang, S. Ren, and J. Sun, · 2016
Cited alongside, same era.
“Wavelet convolutional neural networks for texture classification,”
S. Fujieda, K. Takayama, and T. Hachisuka, · 2017
Cited alongside, same era.
“A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction,”
E. Kang, J. Min, and J.C. Ye, · 2017
Later among the works it cites.
“Faster neural networks straight from jpeg,”
L. Gueguen, A. Sergeev, B. Kadlec, R. Liu, and J. Yosinski, · 2018
Later among the works it cites.
“An end-to-end compression framework based on convolutional neural networks,”
F. Jiang, W. Tao, S. Liu, J. Ren, X. Guo, and D. Zhao, · 2018
Later among the works it cites.
“Towards image understanding from deep compression without decoding,”
R. Torfason, F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, and L. Van Gool, · 2018
Later among the works it cites.
“Quannet: Joint image compression and classification over the channels with limited bandwidth,”
L.D. Chamain, Z. Ding, and S.S. Cheung, · 2019
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