Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges
Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to
support disruptive applications such as extended reality (XR), augmented/virtual reality …
support disruptive applications such as extended reality (XR), augmented/virtual reality …
Real-time detection of apple leaf diseases using deep learning approach based on improved convolutional neural networks
P Jiang, Y Chen, B Liu, D He, C Liang - Ieee Access, 2019 - ieeexplore.ieee.org
Alternaria leaf spot, Brown spot, Mosaic, Grey spot, and Rust are five common types of apple
leaf diseases that severely affect apple yield. However, the existing research lacks an …
leaf diseases that severely affect apple yield. However, the existing research lacks an …
A survey of modulation classification using deep learning: Signal representation and data preprocessing
Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …
management, and control for addressing technical issues, including spectrum awareness …
Automatic modulation classification using CNN-LSTM based dual-stream structure
Z Zhang, H Luo, C Wang, C Gan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Deep learning (DL) has recently aroused substantial concern due to its successful
implementations in many fields. Currently, there are few studies on the applications of DL in …
implementations in many fields. Currently, there are few studies on the applications of DL in …
Grape leaf disease identification using improved deep convolutional neural networks
B Liu, Z Ding, L Tian, D He, S Li, H Wang - Frontiers in Plant Science, 2020 - frontiersin.org
Anthracnose, brown spot, mites, black rot, downy mildew, and leaf blight are six common
grape leaf pests and diseases, which cause severe economic losses to the grape industry …
grape leaf pests and diseases, which cause severe economic losses to the grape industry …
Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …
position in providing Internet access thanks to their freedom of deployment and configuration …
A deep learning framework for optimization of MISO downlink beamforming
Beamforming is an effective means to improve the quality of the received signals in multiuser
multiple-input-single-output (MISO) systems. Traditionally, finding the optimal beamforming …
multiple-input-single-output (MISO) systems. Traditionally, finding the optimal beamforming …
Machine learning for wireless communications in the Internet of Things: A comprehensive survey
Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …
wireless communications than ever before. For this reason, techniques such as spectrum …
NAS-AMR: Neural architecture search-based automatic modulation recognition for integrated sensing and communication systems
Automatic modulation recognition (AMR) technique plays an important role in the
identification of modulation types of unknown signal of integrated sensing and …
identification of modulation types of unknown signal of integrated sensing and …