Knowledgenavigator: Leveraging large language models for enhanced reasoning over knowledge graph
Large language models have achieved outstanding performance on various downstream
tasks with their advanced understanding of natural language and zero-shot capability …
tasks with their advanced understanding of natural language and zero-shot capability …
Federated deep reinforcement learning based trajectory design for UAV-assisted networks with mobile ground devices
Exploiting highly maneuverable unmanned aerial vehicles (UAVs) has been considered as
an efficient way to assist wireless systems, eg, for applications of data collection. However …
an efficient way to assist wireless systems, eg, for applications of data collection. However …
Multivariate time series classification with crucial timestamps guidance
Transformer-based deep learning methods have significantly facilitated multivariate time
series classification (MTSC) tasks. However, due to the inherent operation of self-attention …
series classification (MTSC) tasks. However, due to the inherent operation of self-attention …
Feature representation-based cross-modality shared-specific network and its application in multimode process soft sensing
As the production demand and external environment change, the same production process
may have multiple stable working conditions, ie, multimode process. The traditional process …
may have multiple stable working conditions, ie, multimode process. The traditional process …
[HTML][HTML] Multivariate data binning and examples generation to build a Diabetic Retinopathy classifier based on temporal clinical and analytical risk factors
In this paper, we explore the possibility of exploiting retrospective clinical data from
Electronic Health Records (EHR) for classification tasks in chronic patients. The different …
Electronic Health Records (EHR) for classification tasks in chronic patients. The different …
RFDB: Robust watermarking scheme with Fuzzy-DnCNN using blockchain technique for identity verification
Due to the vast development of computer technology, the security and copyright protection
are the major issues which needs to be addressed. The medical data in one of the most …
are the major issues which needs to be addressed. The medical data in one of the most …
A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology
Among a variety of virtual metrology models, dynamic generative latent variable models
(DGLVMs) have proven to be an effective tool, owing to outstanding advantages in dealing …
(DGLVMs) have proven to be an effective tool, owing to outstanding advantages in dealing …
A deep evidence fusion framework for apple leaf disease classification
Apple leaf disease is one of the main culprits of apple yield reduction. The accurate
classification of apple leaf diseases is essential to reduce economic losses. However …
classification of apple leaf diseases is essential to reduce economic losses. However …
[HTML][HTML] Physics-guided federated learning as an enabler for digital twins
Digital twins bring the potential to increase the efficiency of assets, systems, and processes
by building virtual replicas through real-time data and modeling. However, data are often …
by building virtual replicas through real-time data and modeling. However, data are often …
Filtering offensive language from multilingual social media contents: A deep learning approach
In the face of uncontrolled offensive content on social media, automated detection emerges
as a critical need. This paper tackles this challenge by proposing a novel approach for …
as a critical need. This paper tackles this challenge by proposing a novel approach for …