DeepThink IoT: the strength of deep learning in internet of things
Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …
revolutionized technology in the twenty-first century, enabling humans and machines to …
A review on blockchain smart contracts in the agri-food industry: Current state, application challenges and future trends
With the continuous development of the new crown epidemic and the outbreak of the
Russian-Ukrainian war, the world is facing a serious food crisis, especially the agri-food …
Russian-Ukrainian war, the world is facing a serious food crisis, especially the agri-food …
Ifl-gan: Improved federated learning generative adversarial network with maximum mean discrepancy model aggregation
The generative adversarial network (GAN) is usually built from the centralized, independent
identically distributed (iid) training data to generate realistic-like instances. In real-world …
identically distributed (iid) training data to generate realistic-like instances. In real-world …
AutoInfo GAN: Toward a better image synthesis GAN framework for high-fidelity few-shot datasets via NAS and contrastive learning
J Shi, W Liu, G Zhou, Y Zhou - Knowledge-Based Systems, 2023 - Elsevier
Abstract Background: Generative adversarial networks (GANs) are vital techniques for
synthesizing high-fidelity images. Recent studies have applied them to generation tasks …
synthesizing high-fidelity images. Recent studies have applied them to generation tasks …
The dark side of explanations: Poisoning recommender systems with counterfactual examples
Deep learning-based recommender systems have become an integral part of several online
platforms. However, their black-box nature emphasizes the need for explainable artificial …
platforms. However, their black-box nature emphasizes the need for explainable artificial …
Backdoor attacks against distributed swarm learning
K Chen, H Zhang, X Feng, X Zhang, B Mi, Z Jin - ISA transactions, 2023 - Elsevier
Traditional machine learning approaches often need a central server, where raw datasets or
model updates are trained or aggregated in a centralized way. However, these approaches …
model updates are trained or aggregated in a centralized way. However, these approaches …
MC-LCR: Multimodal contrastive classification by locally correlated representations for effective face forgery detection
As the remarkable development of facial manipulation technologies is accompanied by
severe security concerns, face forgery detection has spurred recent research. Most detection …
severe security concerns, face forgery detection has spurred recent research. Most detection …
Multichannel high noise level ECG denoising based on adversarial deep learning
This paper proposes a denoising method based on an adversarial deep learning approach
for the post-processing of multi-channel fetal electrocardiogram (ECG) signals. As it's well …
for the post-processing of multi-channel fetal electrocardiogram (ECG) signals. As it's well …
Scarcity-GAN: Scarce data augmentation for defect detection via generative adversarial nets
Data augmentation is a crucial and challenging task for improving defect detection with
limited data. Many generative models have been proposed and shown promising …
limited data. Many generative models have been proposed and shown promising …
Tsa-gan: A robust generative adversarial networks for time series augmentation
Time series classification (TSC) is widely used in various real-world applications such as
human activity recognition, smart city governance, etc. Unfortunately, due to different …
human activity recognition, smart city governance, etc. Unfortunately, due to different …