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An Introduction to Image Classification
ISBN-13:
9789819978823
Veröffentl:
2024
Seiten:
290
Autor:
Klaus D. Toennies
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
Image classification is a critical component in computer vision tasks and has numerous applications. Traditional methods for image classification involve feature extraction and classification in feature space. Current state-of-the-art methods utilize end-to-end learning with deep neural networks, where feature extraction and classification are integrated into the model. Understanding traditional image classification is important because many of its design concepts directly correspond to components of a neural network. This knowledge can help demystify the behavior of these networks, which may seem opaque at first sight.
Chapter 1. Image Classification - A Computer Vision Task.- Chapter 2. Image Features - Extraction and Categories.- Chapter 3. Feature Reduction.- Chapter 4. Bayesian Image Classification in Feature Space.- Chapter 5. Distance-based Classifiers.- Chapter 6. Decision Boundaries in Feature Space.- Chapter 7. Multi-layer Perceptron for Image Classification.- Chapter 8. Feature Extraction by Convolutional Neural Network.- Chapter 9. Network Set-up for Image Classification.- Chapter 10. Basic Network Training for Image Classification.- Chapter 11. Dealing with Training Deficiencies.- Chapter 12. Learning Effects and Network Decisions.
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