Adversarial attacks and defenses in machine learning-empowered communication systems and networks: A contemporary survey
Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …
been gaining significant attention due to the rapidly growing applications of deep learning in …
Edge AI for Internet of Energy: Challenges and perspectives
The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
Beyond efficiency: A systematic survey of resource-efficient large language models
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated
models like OpenAI's ChatGPT, represents a significant advancement in artificial …
models like OpenAI's ChatGPT, represents a significant advancement in artificial …
A survey on deep learning hardware accelerators for heterogeneous hpc platforms
Recent trends in deep learning (DL) imposed hardware accelerators as the most viable
solution for several classes of high-performance computing (HPC) applications such as …
solution for several classes of high-performance computing (HPC) applications such as …
Afibri-net: A lightweight convolution neural network based atrial fibrillation detector
N Phukan, MS Manikandan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
By considering limited resource-constraints of medical devices and advanced deep learning
networks, in this paper, we explore a lightweight convolutional neural network (CNN) based …
networks, in this paper, we explore a lightweight convolutional neural network (CNN) based …
Photonic neural networks based on integrated silicon microresonators
Recent progress in artificial intelligence (AI) has boosted the computational possibilities in
fields in which standard computers are not able to perform adequately. The AI paradigm is to …
fields in which standard computers are not able to perform adequately. The AI paradigm is to …
Neural network methods for radiation detectors and imaging
Recent advances in image data proccesing through deep learning allow for new
optimization and performance-enhancement schemes for radiation detectors and imaging …
optimization and performance-enhancement schemes for radiation detectors and imaging …
Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge
Including Artificial Neural Networks in embedded systems at the edge allows applications to
exploit Artificial Intelligence capabilities directly within devices operating at the network …
exploit Artificial Intelligence capabilities directly within devices operating at the network …
A review on deepfake generation and detection: bibliometric analysis
Deepfake refers to an artificial intelligence-based technique to produce manipulated videos
that look realistic. However, this good aspect of Deepfake sometimes pose serious threats to …
that look realistic. However, this good aspect of Deepfake sometimes pose serious threats to …
Design and Optimization of Residual Neural Network Accelerators for Low-Power FPGAs Using High-Level Synthesis
Residual neural networks are widely used in computer vision tasks. They enable the
construction of deeper and more accurate models by mitigating the vanishing gradient …
construction of deeper and more accurate models by mitigating the vanishing gradient …