Back to Search
Start Over
Discriminative Fast Hierarchical Learning for Multiclass Image Classification
- Source :
- IEEE Transactions on Neural Networks and Learning Systems. 31:2779-2790
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- In this article, a discriminative fast hierarchical learning algorithm is developed for supporting multiclass image classification, where a visual tree is seamlessly integrated with multitask learning to achieve fast training of the tree classifier hierarchically (i.e., a set of structural node classifiers over the visual tree). By partitioning a large number of categories hierarchically in a coarse-to-fine fashion, a visual tree is first constructed and further used to handle data imbalance and identify the interrelated learning tasks automatically (e.g., the tasks for learning the node classifiers for the sibling child nodes under the same parent node are strongly interrelated), and a multitask SVM classifier is trained for each nonleaf node to achieve more effective separation of its sibling child nodes at the next level of the visual tree. Both the internode visual similarities and the interlevel visual correlations are utilized to train more discriminative multitask SVM classifiers and control the interlevel error propagation effectively, and a stochastic gradient descent (SGD) algorithm is developed for learning such multitask SVM classifiers with higher efficiency. Our experimental results have demonstrated that our fast hierarchical learning algorithm can achieve very competitive results on both the classification accuracy rates and the computational efficiency.
- Subjects :
- Contextual image classification
Computer Networks and Communications
business.industry
Computer science
Deep learning
Multi-task learning
Pattern recognition
02 engineering and technology
Computer Science Applications
Visualization
Support vector machine
ComputingMethodologies_PATTERNRECOGNITION
Stochastic gradient descent
Discriminative model
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
business
Classifier (UML)
Software
Subjects
Details
- ISSN :
- 21622388 and 2162237X
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Neural Networks and Learning Systems
- Accession number :
- edsair.doi.dedup.....013af376af24cbe120ae26b180183459