Deep Joint Source-Channel Coding of Images with Feedback
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[1] Deniz Gündüz,et al. Successive Refinement of Images with Deep Joint Source-Channel Coding , 2019, 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).
[2] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[3] Sreeram Kannan,et al. DEEPTURBO: Deep Turbo Decoder , 2019, 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).
[4] Claude E. Shannon,et al. Two-way Communication Channels , 1961 .
[5] Deniz Gündüz,et al. Joint Source–Channel Codes for MIMO Block-Fading Channels , 2007, IEEE Transactions on Information Theory.
[6] Sreeram Kannan,et al. LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks , 2018, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).
[7] David Minnen,et al. Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[8] Hamid Jafarkhani,et al. Joint source-channel coding of images for channels with feedback , 1998 .
[9] David Minnen,et al. Joint Autoregressive and Hierarchical Priors for Learned Image Compression , 2018, NeurIPS.
[10] David Burshtein,et al. Deep Learning Methods for Improved Decoding of Linear Codes , 2017, IEEE Journal of Selected Topics in Signal Processing.
[11] Aria Nosratinia,et al. Progressive joint source-channel coding in feedback channels , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).
[12] Lucas Theis,et al. Lossy Image Compression with Compressive Autoencoders , 2017, ICLR.
[13] Valero Laparra,et al. Density Modeling of Images using a Generalized Normalization Transformation , 2015, ICLR.
[14] H.-S. Philip Wong,et al. Joint Source-Channel Coding with Neural Networks for Analog Data Compression and Storage , 2018, 2018 Data Compression Conference.
[15] Mikael Skoglund,et al. Design and performance of VQ-based hybrid digital-analog joint source-channel codes , 2002, IEEE Trans. Inf. Theory.
[16] Jakob Hoydis,et al. An Introduction to Deep Learning for the Physical Layer , 2017, IEEE Transactions on Cognitive Communications and Networking.
[17] Andrea J. Goldsmith,et al. Deep Learning for Joint Source-Channel Coding of Text , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[18] J. Pieter M. Schalkwijk,et al. A coding scheme for additive noise channels with feedback-II: Band-limited signals , 1966, IEEE Trans. Inf. Theory.
[19] Claude E. Shannon,et al. The zero error capacity of a noisy channel , 1956, IRE Trans. Inf. Theory.
[20] Sergio Verdú,et al. The source-channel separation theorem revisited , 1995, IEEE Trans. Inf. Theory.
[21] P. Viswanath,et al. Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels , 2019, NeurIPS.
[22] Andrea Goldsmith,et al. Neural Network Detection of Data Sequences in Communication Systems , 2018, IEEE Transactions on Signal Processing.
[23] Sergio Verdú,et al. Joint source-channel coding with feedback , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).
[24] Polina Bayvel,et al. End-to-End Deep Learning of Optical Fiber Communications , 2018, Journal of Lightwave Technology.
[25] V. Kafedziski. Joint source channel coding of images over frequency selective fading channels with feedback using DCT and multicarrier block pulse amplitude modulation , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).
[26] David Minnen,et al. Variational image compression with a scale hyperprior , 2018, ICLR.
[27] Mikael Skoglund,et al. Soft Decoding for Vector Quantization Over Noisy Channels with Memory , 1999, IEEE Trans. Inf. Theory.
[28] Touradj Ebrahimi,et al. Perceptual Quality Study on Deep Learning Based Image Compression , 2019, 2019 IEEE International Conference on Image Processing (ICIP).
[29] Jooyoung Lee,et al. Context-adaptive Entropy Model for End-to-end Optimized Image Compression , 2018, ICLR.
[30] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[31] Nariman Farvardin,et al. On the performance and complexity of channel-optimized vector quantizers , 1991, IEEE Trans. Inf. Theory.
[32] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[33] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[34] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[35] Andrea J. Goldsmith,et al. Source and Channel Coding for Correlated Sources Over Multiuser Channels , 2008, IEEE Transactions on Information Theory.
[36] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[37] Tor A. Ramstad,et al. Shannon-kotel-nikov mappings in joint source-channel coding , 2009, IEEE Transactions on Communications.
[38] Nam C. Phamdo,et al. Hybrid digital-analog (HDA) joint source-channel codes for broadcasting and robust communications , 2002, IEEE Trans. Inf. Theory.
[39] S. Butman. Rate distortion over band-limited feedback channels , 1971 .
[40] Sreeram Kannan,et al. Deepcode: Feedback Codes via Deep Learning , 2018, IEEE Journal on Selected Areas in Information Theory.
[41] Mikael Skoglund,et al. On channel-constrained vector quantization and index assignment for discrete memoryless channels , 1999, IEEE Trans. Inf. Theory.
[42] Deniz Gündüz,et al. Deep Joint Source-channel Coding for Wireless Image Transmission , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[43] Kannan Ramchandran,et al. Robust image transmission over energy-constrained time-varying channels using multiresolution joint source-channel coding , 1998, IEEE Trans. Signal Process..
[44] Thomas Kailath,et al. An application of Shannon's rate-distortion theory to analog communication over feedback channels , 1967 .
[45] David Minnen,et al. Variable Rate Image Compression with Recurrent Neural Networks , 2015, ICLR.
[46] Michael Gastpar,et al. To code, or not to code: lossy source-channel communication revisited , 2003, IEEE Trans. Inf. Theory.
[47] Valero Laparra,et al. End-to-end Optimized Image Compression , 2016, ICLR.
[48] Nariman Farvardin,et al. A study of vector quantization for noisy channels , 1990, IEEE Trans. Inf. Theory.
[49] Stephan ten Brink,et al. Deep Learning-Based Polar Code Design , 2019, 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[50] Leo I. Bluestein,et al. Transmission of analog waveforms through channels with feedback (Corresp.) , 1967, IEEE Trans. Inf. Theory.
[51] Avideh Zakhor,et al. Bit allocation for joint source/channel coding of scalable video , 2000, IEEE Trans. Image Process..