[IP3-4-6] Deep learning

Deep learning approaches have classically been divided into spatial learning (for example, convolutional neural networks for object classification) and sequence learning (for example, speech recognition)

Introduction

External resources

• Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G., & Johnson, B. A. (2019). Deep learning in remote sensing applications: A meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 166-177. doi:https://doi.org/10.1016/j.isprsjprs.2019.04.015
• Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., Prabhat, 2019. Deep learning and process understanding for data-driven Earth system science. Nature 566, 195-204.

Learning outcomes

• 2306 - Compare different deep learning approaches in EO image classification

  Compare different deep learning approaches in EO image classification

Self assessment

Outgoing relations

• [IP3-4-6] Deep learning is subconcept of [IP3-4] Image classification

Incoming relations

• [IP3-4-6-1] Convolutional neural networks (CNN) is subconcept of [IP3-4-6] Deep learning