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Modular Neural Networks
We describe in this chapter the basic concepts, theory and algorithms of modular and ensemble neural networks. We will also give particular attention...
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Type-1 Fuzzy Logic
This chapter introduces the basic concepts, notation, and basic operations for the type-1 fuzzy sets that will be needed in the following chapters....
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Human Recognition using Face, Fingerprint and Voice
We describe in this chapter a new approach for human recognition using as information the face, fingerprint, and voice of a person. We have described...
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Fingerprint Recognition with Modular Neural Networks and Fuzzy Measures
We describe in this chapter a new approach for fingerprint recognition using modular neural networks with a fuzzy logic method for response...
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Voice Recognition with Neural Networks, Fuzzy Logic and Genetic Algorithms
We describe in this chapter the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case...
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Clustering with Intelligent Techniques
Cluster analysis is a technique for grou** data and finding structures in data. The most common application of clustering methods is to partition a...
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Introduction to Pattern Recognition with Intelligent Systems
We describe in this book, new methods for intelligent pattern recognition using soft computing techniques. Soft Computing (SC) consists of several...
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Supervised Learning Neural Networks
In this chapter, we describe the basic concepts, notation, and basic learning algorithms for supervised neural networks that will be of great use for...
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Evolutionary Computing for Architecture Optimization
This chapter introduces the basic concepts and notation of evolutionary algorithms, which are basic search methodologies that can be used for...
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Intuitionistic and Type-2 Fuzzy Logic
We describe in this chapter two new areas in fuzzy logic, type-2 fuzzy logic systems and intuitionistic fuzzy logic. Basically, a type-2 fuzzy set is...
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Face Recognition with Modular Neural Networks and Fuzzy Measures
We describe in this chapter a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We...
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Unsupervised Learning Neural Networks
This chapter introduces the basic concepts and notation of unsupervised learning neural networks. Unsupervised networks are useful for analyzing data...
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End-to-End Video Text Spotting with Transformer
Recent video text spotting methods usually require the three-staged pipeline, i.e., detecting text in individual images, recognizing localized text,...
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Research on gesture segmentation method based on FCN combined with CBAM-ResNet50
As a key step of gesture recognition, gesture segmentation can effectively reduce the impact of complex backgrounds on recognition results and...
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Reduction of the noise effects in phase images using a motorized dual-wavelength quantitative phase microscope
This article introduces a novel method that leads to the reduction of noise effects and improvement in the quality of phase image acquisition in...
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Multi-modal Prototypes for Open-World Semantic Segmentation
In semantic segmentation, generalizing a visual system to both seen categories and novel categories at inference time has always been practically...
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3D Reconstruction of flame temperature field based on lightweight residual network with spatial attention mechanism
Flame temperature field measurement has always been a key topic in combustion research, which is of great significance for combustion state diagnosis...
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Learning Feature Restoration Transformer for Robust Dehazing Visual Object Tracking
In recent years, deep-learning-based visual object tracking has obtained promising results. However, a drastic performance drop is observed when...
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CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between...
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Adaptive shift graph convolutional neural network for hand gesture recognition based on 3D skeletal similarity
Graph convolutional neural networks (GCNs) have shown promising results in the field of hand gesture recognition based on 3D skeletal data. However,...
