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Image Analysis and Recognition

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Cover of 'Image Analysis and Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Weighted Fisher Discriminant Analysis in the Input and Feature Spaces
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    Chapter 2 Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces
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    Chapter 3 Parallel Implementation of the DRLSE Algorithm
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    Chapter 4 A Multiscale Energy-Based Time-Domain Approach for Interference Detection in Non-stationary Signals
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    Chapter 5 SMAT: Smart Multiple Affinity Metrics for Multiple Object Tracking
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    Chapter 6 Combining Mixture Models and Spectral Clustering for Data Partitioning
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    Chapter 7 MSPNet: Multi-level Semantic Pyramid Network for Real-Time Object Detection
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    Chapter 8 Multi-domain Document Layout Understanding Using Few-Shot Object Detection
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    Chapter 9 Object Tracking Through Residual and Dense LSTMs
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    Chapter 10 Theoretical Insights into the Use of Structural Similarity Index in Generative Models and Inferential Autoencoders
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    Chapter 11 Efficient Prediction of Gold Prices Using Hybrid Deep Learning
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    Chapter 12 Exploring Information Theory and Gaussian Markov Random Fields for Color Texture Classification
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    Chapter 13 Anomaly Detection for Images Using Auto-encoder Based Sparse Representation
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    Chapter 14 A Framework for Fusion of T1-Weighted and Dynamic MRI Sequences
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    Chapter 15 Contributions to a Quantitative Unsupervised Processing and Analysis of Tongue in Ultrasound Images
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    Chapter 16 Improving Multiple Sclerosis Lesion Boundaries Segmentation by Convolutional Neural Networks with Focal Learning
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    Chapter 17 B-Mode Ultrasound Breast Anatomy Segmentation
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    Chapter 18 Enhancing the Prediction of Lung Cancer Survival Rates Using 2D Features from 3D Scans
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    Chapter 19 Lesion Localization in Paediatric Epilepsy Using Patch-Based Convolutional Neural Network
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    Chapter 20 Deep Learning Models for Segmentation of Mobile-Acquired Dermatological Images
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    Chapter 21 Semi-automatic Tool to Identify Heterogeneity Zones in LGE-CMR and Incorporate the Result into a 3D Model of the Left Ventricle
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    Chapter 22 A Deep Learning Based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
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    Chapter 23 Studying the Effect of Digital Stain Separation of Histopathology Images on Image Search Performance
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    Chapter 24 Generalized Multiple Instance Learning for Cancer Detection in Digital Histopathology
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    Chapter 25 A Multi-dataset Approach for DME Risk Detection in Eye Fundus Images
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    Chapter 26 Enhancement of Retinal Fundus Images via Pixel Color Amplification
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    Chapter 27 Wavelet-Based Retinal Image Enhancement
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    Chapter 28 An Interpretable Data-Driven Score for the Assessment of Fundus Images Quality
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    Chapter 29 Optic Disc and Fovea Detection in Color Eye Fundus Images
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    Chapter 30 The Effect of Menopause on the Sexual Dimorphism in the Human Retina – Texture Analysis of Optical Coherence Tomography Data
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    Chapter 31 Deep Retinal Diseases Detection and Explainability Using OCT Images
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    Chapter 32 An Automated Workflow for Lung Nodule Follow-Up Recommendation Using Deep Learning
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    Chapter 33 Pulmonary-Nodule Detection Using an Ensemble of 3D SE-ResNet18 and DPN68 Models
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    Chapter 34 3DCNN for Pulmonary Nodule Segmentation and Classification
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    Chapter 35 Residual Networks for Pulmonary Nodule Segmentation and Texture Characterization
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    Chapter 36 Automatic Lung Cancer Follow-Up Recommendation with 3D Deep Learning
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    Chapter 37 Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung
Overall attention for this book and its chapters
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Title
Image Analysis and Recognition
Published by
Springer International Publishing, January 2020
DOI 10.1007/978-3-030-50516-5
ISBNs
978-3-03-050515-8, 978-3-03-050516-5
Editors

Aurélio Campilho, Fakhri Karray, Zhou Wang

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