  During the last decade, several research works have focused on providing
novel deep learning methods in many application fields. However, few of them
have investigated the weight initialization process for deep learning, although
its importance is revealed in improving deep learning performance. This can be
justified by the technical difficulties in proposing new techniques for this
promising research field. In this paper, a survey related to weight
initialization techniques for deep algorithms in remote sensing is conducted.
This survey will help practitioners to drive further research in this promising
field. To the best of our knowledge, this paper constitutes the first survey
focusing on weight initialization for deep learning models.
