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Investigating the Use of Belief-Bias to Measure Acceptance of False Information
Belief-bias occurs when individuals’ prior beliefs impact their ability to judge the validity (i.e., structure) of an argument such that they are...
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Threat Mitigation Model with Low False Alarm Rate Based on Hybrid Deep Belief Network
Most Deep Learning techniques propose solutions against Distributed Denial of Service (DDoS) attacks by leveraging networking enhanced programming...
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Reports, Observations, and Belief Change
We consider belief change in a context where information comes from reports, and the reporting agents may not be honest. In order to capture this...
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A knowledge compilation perspective on queries and transformations for belief tracking
Nondeterministic planning is the process of computing plans or policies of actions achieving given goals, when there is nondeterministic uncertainty...
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A novel approach for detection of APT malware using multi-dimensional hybrid Bayesian belief network
Due to the continuous evolution of adversary tactics, strategies, and processes, the contemporary digital universe is confronted with new obstacles...
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Belief Reconfiguration
We study a generalisation of iterated belief revision in a setting where we keep track not only of the received information (in the form of messages)...
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Adaptive isomap feature extractive gradient deep belief network classifier for diabetic retinopathy identification
Diabetic retinopathy (DR) is an infection that bases eternal visualization loss in patients with diabetes mellitus. With DR, the glucose level in the...
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Deep Belief Bayesian Joint Conditional Detection of coronary artery plaque and stenosis in X-ray angiography images
Numerous classes of plaque and differing grades of stenosis could give rise to distinct patient management with coronary artery disease. As a...
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An optimized deep belief system for heart disease classification and severity prediction
Artificial Intelligence (AI) is applicable in many digital applications such as education, medical, transactions, etc.; it has afforded the finest...
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An improved ensemble deep belief model (EDBM) for pap-smear cell image classification
Applications of deep learning models for medical image analysis have been concentrated in recent years. This study presents an improved automatic...
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SDESA: secure cloud computing with gradient deep belief network and congruential advanced encryption
With the aim to enhance cloud security with higher data confidentiality rate and integrity, we propose a novel technique called Stochastic Deep...
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Hubs of belief networks across sociodemographic and ideological groups
Beliefs are essential components of the human mind, as they define personal identity, integration and adaptation to social groups. Most theoretical...
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KFDBN: Kernelized Finetuned Deep Belief Network for recommendation
In today’s technologically evolved world, users have become accustomed to personalized tools that provide accurate and precise recommendations that...
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An online intrusion detection method for industrial control systems based on extended belief rule base
Intrusion detection in industrial control systems (ICS) is crucial for maintaining the security of physical information systems. However, the...
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A better and fast cloud intrusion detection system using improved squirrel search algorithm and modified deep belief network
Utilizing the cloud environment is one of the most preferable option in every information technology (IT) organization for running its business due...
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An improved detection of blind image forgery using hybrid deep belief network and adaptive fuzzy clustering
Blind image forgery prediction in the field of image forgery is difficult. Hence, it is the major attention for the investigators recently. This work...
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Neonatal seizure detection using deep belief networks from multichannel EEG data
Seizures in neonates happen to be one of the most difficult emergency circumstances to deal with. They are the first signs of significant...
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Integrating Evolutionary Prejudices in Belief Function Theory
This paper deals with belief change in the framework of Dempster-Shafer theory in the context where an agent has a prejudice, i.e., a priori...
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Automatic approach for breast cancer detection based on deep belief network using histopathology images
Histopathological images play an essential role in breast cancer diagnosis, prognosis, and treatment planning. Early and accurate diagnosis leads to...
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Joint contrastive learning and belief rule base for named entity recognition in cybersecurity
Named Entity Recognition (NER) in cybersecurity is crucial for mining information during cybersecurity incidents. Current methods rely on pre-trained...
