Empirical Performance of Deep Learning Models with Class Imbalance for Crop Disease Classification
- 21 August 2024
- book chapter
- Published by Springer Nature
- p. 118-135
Abstract
No abstract availableKeywords
This publication has 26 references indexed in Scilit:
- Deep learning methods for biotic and abiotic stresses detection and classification in fruits and vegetables: State of the art and perspectivesArtificial Intelligence in Agriculture, 2023
- Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research DirectionsSN Computer Science, 2021
- An Overview of Overfitting and its SolutionsJournal of Physics: Conference Series, 2019
- A systematic study of the class imbalance problem in convolutional neural networksNeural Networks, 2018
- On the Impact of Imbalanced Data in Convolutional Neural Networks Performance2017
- Practical Recommendations for Gradient-Based Training of Deep Architectures2012
- Evaluating Learning Algorithms2011
- On the Expressive Power of Deep Architectures2011
- An introduction to ROC analysisPattern Recognition Letters, 2006
- Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation2006