Browsing Institute of New Imaging Technologies (INIT) by Keyword "deep metric learning"
Now showing items 1-4 of 4
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Generalized Scalable Neighborhood Component Analysis for Single and Multi-Label Remote Sensing Image Characterization
IEEE (2021)Deep metric learning has recently become a prominent technology for the semantic understanding ofremote sensing (RS) scenes due to its great potential for characterizing visual semantics. However, state-of-the-art deep ... -
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
MDPI (2020)Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic ... -
Noise-Tolerant Deep Neighborhood Embedding for Remotely Sensed Images With Label Noise
IEEE (2021-02-02)Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. Most of the adopted loss functions for training these models require accurate annotations. ... -
Rotation-Invariant Deep Embedding for Remote Sensing Images
Institute of Electrical and Electronics Engineers (2021-06-28)Endowing convolutional neural networks (CNNs) with the rotation-invariant capability is important for characterizing the semantic contents of remote sensing (RS) images since they do not have typical orientations. Most of ...