An incremental-learning neural network for the classification of remote-sensing images

By Lorenzo Bruzzone, Diego Fernández-Prieto. 1999

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Gaston Lenczner
2. Onur Tasar
3. Bertrand Le Saux
4. Adrien Chan-Hon-Tong
5. Nicola Luminari
6. Pierre Alliez
7. Yuliya Tarabalka
8. Biplab Banerjee

Citations in the corpus

• Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data (2018, background): “Even before neural networks have become popular, research works had been studying this issue [12]–[15].”
• Weakly-Supervised Continual Learning for Class-Incremental Segmentation (2022, background): “This problem was already considered two decades ago [8] and two main pitfalls are identified.”
• CILEA-NET: Curriculum-Based Incremental Learning Framework for Remote Sensing Image Classification (2021, methodology): “In contrast, in [14] and [15], it was suggested to use SVM-and RBF-based networks, respectively, for training a model in the incremental setting.”