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Found 13 papers, 0 papers with code
Within the Lack of COVID-19 Benchmark Dataset: A Novel GAN with Deep Transfer Learning for Corona-virus Detection in Chest X-ray Images
In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85. 2% in testing accuracy, while in the third scenario which includes 2 classes (COVID-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99. 9% in the validation accuracy.
Improved Definition of NonStandard Neutrosophic Logic and Introduction to Neutrosophic Hyperreals
O the third version of this response-paper to Imamura criticism, we recall that NonStandard Neutrosophic Logic was never used by neutrosophic community in no application, that the quarter of century old neutrosophic operators (1995) criticized by Imamura were never utilized since they were improved shortly after but he omits to tell their development, and that in real world applications we need to convert/approximate the NonStandard Analysis hyperreals, monads and binads to tiny intervals with the desired accuracy, otherwise they would be inapplicable.
Plithogeny, Plithogenic Set, Logic, Probability, and Statistics
In order to obtain a better accuracy for the plithogenic aggregation operators in the plithogenic set, logic, probability and for a more exact inclusion (partial order), a (fuzzy, intuitionistic fuzzy, or neutrosophic) contradiction (dissimilarity) degree is defined between each attribute value and the dominant (most important) attribute value.
New Trends in Neutrosophic Theory and Applications
The book New Trends in Neutrosophic Theories and Applications focuses on theories, methods, algorithms for decision making and also applications involving neutrosophic information.
Strong Neutrosophic Graphs and Subgraph Topological Subspaces
Further special lattice graph of subgraphs of these graphs are defined and described.
Neutrosophic Overset, Neutrosophic Underset, and Neutrosophic Offset. Similarly for Neutrosophic Over-/Under-/Off- Logic, Probability, and Statistics
were extended to respectively Neutrosophic Over-/Under-/Off-Logic, -Measure, -Probability, -Statistics etc.
Symbolic Neutrosophic Theory
We construct examples of splitting the literal indeterminacy (I) into literal subindeterminacies (I1, I2, and so on, Ir), and to define a multiplication law of these literal subindeterminacies in order to be able to build refined I neutrosophic algebraic structures.
Unification of Fusion Theories, Rules, Filters, Image Fusion and Target Tracking Methods (UFT)
The author has pledged in various papers, conference or seminar presentations, and scientific grant applications (between 2004-2015) for the unification of fusion theories, combinations of fusion rules, image fusion procedures, filter algorithms, and target tracking methods for more accurate applications to our real world problems - since neither fusion theory nor fusion rule fully satisfy all needed applications.
Soft Neutrosophic Algebraic Structures and Their Generalization
Algebraic structures using soft set theory are very rapidly developed.
n-Valued Refined Neutrosophic Logic and Its Applications to Physics
In this paper we present a short history of logics: from particular cases of 2-symbol or numerical valued logic to the general case of n-symbol or numerical valued logic.
Introduction to Neutrosophic Statistics
Also, there are population or sample individuals whose data could be indeterminate.
Introduction to Neutrosophic Measure, Neutrosophic Integral, and Neutrosophic Probability
In this paper, we introduce for the first time the notions of neutrosophic measure and neutrosophic integral, and we develop the 1995 notion of neutrosophic probability.
$α$-Discounting Multi-Criteria Decision Making ($α$-D MCDM)
In the current book we propose the Fairness Principle, i. e. each coefficient should be discounted with the same percentage (we think this is fair: not making any favoritism or unfairness to any coefficient), but the reader can propose other principles.
