Fuzzy Sets Methods in Image Processing and Understanding
Medical Imaging Applications
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Chapter and Conference Paper
Initialization and Plasticity of CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm
The CEFYDRA is a network of units whose outputs are obtained using a fuzzy Takagi-Sugeno-Kang approach. At each unit, the information is clustered in fuzzy sets and then mapped using logistic functions and Cau...
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Chapter and Conference Paper
Latent Semantic Structure in Malicious Programs
Latent Semantic Analysis is a method of matrix decomposition used for discovering topics and topic weights in natural language documents. This study uses Latent Semantic Analysis to analyze the composition bin...
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Chapter
Extension to Multidimensional Problems of a Fuzzy-Based Explainable and Noise-Resilient Algorithm
While Deep Neural Networks (DNNs) have shown incredible performance in a variety of data, they are brittle and opaque: easily fooled by the presence of noise, and difficult to understand the underlying reasoning ...
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Chapter and Conference Paper
Bridging the Resource Gap in Cross-Lingual Embedding Space
The map** based methods for inducing a cross-lingual embedding space involves learning a linear map** from the individual monolingual embedding spaces to a shared semantic space where English is often chos...
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Chapter and Conference Paper
Why Sine Membership Functions
In applications of fuzzy techniques to several practical problems – in particular, to the problem of predicting passenger flows in the airports – the most efficient membership function is a sine function; to b...
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Chapter
Preliminaries
This chapter introduces some concepts, notations, and terminology, which will be useful subsequently in this book. Section 2.1 summarizes the main sources of imprecision in the context of image processing and ...
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Chapter
Fuzzy Mathematical Morphology
In this chapter, we present the theory of fuzzy mathematical morphology, starting from the algebraic notions, the basic operators, and providing some examples of derived operators. Extending mathematical morph...
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Chapter
Spatial Relations
In this chapter we move to more structural information, expressed in terms of spatial relationships between objects or fuzzy objects.
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Chapter and Conference Paper
Single Hidden Layer CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm
This paper summarizes the mathematical demonstration of the update rules for the first hidden layer of a double-layered network of cluster-first fuzzy-based regression algorithms. The proposed architecture is ...
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Chapter
Structural and Linguistic Representations
In this chapter, some formal models for knowledge and information representation are presented, focusing on their extensions to fuzzy sets. They will be used for image understanding in Chap. 9
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Chapter
Introduction
Since its introduction (Zadeh, Inf Control 8:338–353, 1965), fuzzy sets theory was rapidly exploited and further developed for image processing and image understanding problems. One reason for this development...
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Chapter
Fuzzy Spatial Objects
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Chapter and Conference Paper
Multiple Hidden Layered CEFYDRA: Cluster-First Explainable Fuzzy-Based Deep Self-reorganizing Algorithm
We propose a deep learning algorithm that breaks with the paradigm of weights and activation functions, CEFYDRA, a network of cluster-first fuzzy-based regression algorithms. In this paper, we cover the genera...
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Chapter
Fusion
Fusion has emerged as an important aspect of information processing in several very different fields. This chapter addresses the question of information fusion under imprecision, in the domain of image process...
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Chapter
Fuzzy Sets and Machine Learning
The issue of learning is central to fuzzy set based methods. What we mean by this is that while the notion on a fuzzy set is natural and easy to grasp, for applications, the actual membership function must be ...
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Chapter
Structural and Linguistic Reasoning for Image Understanding
A well-known problem in image and computer vision is the semantic gap (see Sect. 8.1.3) between the physical level of images, that is features extracted by image processing, a...
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Book
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Article
Open AccessBio-informatic analysis of CRISPR protospacer adjacent motifs (PAMs) in T4 genome
The existence of protospacer adjacent motifs (PAMs) sequences in bacteriophage genome is critical for the recognition and function of the clustered regularly interspaced short palindromic repeats-Cas (CRISPR-C...
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Chapter
Localized Learning: A Possible Alternative to Current Deep Learning Techniques
At present, the most efficient deep learning technique is the use of deep neural networks. However, recent empirical results show that in some situations, it is even more efficient to use “localized” learning—...
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Chapter and Conference Paper
Context for API Calls in Malware vs Benign Programs
The current progress in computer technology is matched by the increase in the malware and cyber-attacks, resulting in a nearly constant battle between establishing a complete malware detection technique and ne...
