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An Introduction to Image Classification From Designed Models to End-to-End Learning /

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, wh...

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Détails bibliographiques
Auteur principal: Toennies, Klaus D. (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:anglais
Publié: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Édition:1st ed. 2024.
Sujets:
Computer vision.
Machine learning.
Pattern recognition systems.
Biometric identification.
Artificial intelligence > Data processing.
Computer Vision.
Machine Learning.
Automated Pattern Recognition.
Biometrics.
Data Science.
Accès en ligne:https://doi.org/10.1007/978-981-99-7882-3
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Table des matières:
  • 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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