Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

[HTML][HTML] When 5G meets deep learning: a systematic review

GL Santos, PT Endo, D Sadok, J Kelner - Algorithms, 2020 - mdpi.com
This last decade, the amount of data exchanged on the Internet increased by over a
staggering factor of 100, and is expected to exceed well over the 500 exabytes by 2020. This …

Wireless image transmission using deep source channel coding with attention modules

J Xu, B Ai, W Chen, A Yang, P Sun… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Recent research on joint source channel coding (JSCC) for wireless communications has
achieved great success owing to the employment of deep learning (DL). However, the …

DeepJSCC-f: Deep Joint Source-Channel Coding of Images With Feedback

DB Kurka, D Gündüz - IEEE journal on selected areas in …, 2020 - ieeexplore.ieee.org
We consider wireless transmission of images in the presence of channel output feedback.
From a Shannon theoretic perspective feedback does not improve the asymptotic end-to …

Turbo autoencoder: Deep learning based channel codes for point-to-point communication channels

Y Jiang, H Kim, H Asnani, S Kannan… - Advances in neural …, 2019 - proceedings.neurips.cc
Designing codes that combat the noise in a communication medium has remained a
significant area of research in information theory as well as wireless communications …

Fpga-based deep learning inference accelerators: Where are we standing?

A Nechi, L Groth, S Mulhem, F Merchant… - ACM Transactions on …, 2023 - dl.acm.org
Recently, artificial intelligence applications have become part of almost all emerging
technologies around us. Neural networks, in particular, have shown significant advantages …

Crsf: An intrusion detection framework for industrial internet of things based on pretrained cnn2d-rnn and svm

S Li, G Chai, Y Wang, G Zhou, Z Li, D Yu, R Gao - IEEE Access, 2023 - ieeexplore.ieee.org
The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …

Ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning

AV Makkuva, X Liu, MV Jamali… - International …, 2021 - proceedings.mlr.press
Landmark codes underpin reliable physical layer communication, eg, Reed-Muller, BCH,
Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a …

Physical layer communication via deep learning

H Kim, S Oh, P Viswanath - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …