AI models for green communications towards 6G
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
Differential privacy techniques for cyber physical systems: A survey
MU Hassan, MH Rehmani… - … Communications Surveys & …, 2019 - ieeexplore.ieee.org
Modern cyber physical systems (CPSs) has widely being used in our daily lives because of
development of information and communication technologies (ICT). With the provision of …
development of information and communication technologies (ICT). With the provision of …
ConvUNeXt: An efficient convolution neural network for medical image segmentation
Recently, ConvNeXts constructing from standard ConvNet modules has produced
competitive performance in various image applications. In this paper, an efficient model …
competitive performance in various image applications. In this paper, an efficient model …
A hybrid blockchain-based identity authentication scheme for multi-WSN
Z Cui, XUE Fei, S Zhang, X Cai, Y Cao… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) equipment is usually in a harsh environment, and its security has
always been a widely concerned issue. Node identity authentication is an important means …
always been a widely concerned issue. Node identity authentication is an important means …
Personalized recommendation system based on collaborative filtering for IoT scenarios
Z Cui, X Xu, XUE Fei, X Cai, Y Cao… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recommendation technology is an important part of the Internet of Things (IoT) services,
which can provide better service for users and help users get information anytime …
which can provide better service for users and help users get information anytime …
IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture
The volume, type, and sophistication of malware is increasing. Deep convolutional neural
networks (CNNs) have lately proven their effectiveness in malware binary detection through …
networks (CNNs) have lately proven their effectiveness in malware binary detection through …
[HTML][HTML] High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images
In this study, multiple lung diseases are diagnosed with the help of the Neural Network
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
[HTML][HTML] An improved transformer network for skin cancer classification
C Xin, Z Liu, K Zhao, L Miao, Y Ma, X Zhu… - Computers in Biology …, 2022 - Elsevier
Background Use of artificial intelligence to identify dermoscopic images has brought major
breakthroughs in recent years to the early diagnosis and early treatment of skin cancer, the …
breakthroughs in recent years to the early diagnosis and early treatment of skin cancer, the …
Bio-inspired computation: Where we stand and what's next
In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
[HTML][HTML] An efficient densenet-based deep learning model for malware detection
Recently, there has been a huge rise in malware growth, which creates a significant security
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …