Remote sensing image retrieval in the past decade: Achievements, challenges, and future directions
Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest
from a large remote sensing image archive, which has remained to be a hot topic over the …
from a large remote sensing image archive, which has remained to be a hot topic over the …
PCLUDA: A pseudo-label consistency learning-based unsupervised domain adaptation method for cross-domain optical remote sensing image retrieval
D Hou, S Wang, X Tian, H Xing - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent advances in deep learning have dramatically improved the performance of content-
based remote sensing image retrieval (CBRSIR) with the same distribution of training set …
based remote sensing image retrieval (CBRSIR) with the same distribution of training set …
An analysis on deep learning approaches: addressing the challenges in remote sensing image retrieval
SK Sudha, S Aji - International Journal of Remote Sensing, 2021 - Taylor & Francis
ABSTRACT A considerable volume of high-resolution remote sensing (HRRS) data is
generated with the intense space explorations happening globally. Remote sensing image …
generated with the intense space explorations happening globally. Remote sensing image …
OSAP‐Loss: Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval
In existing remote sensing image retrieval (RSIR) datasets, the number of images among
different classes varies dramatically, which leads to a severe class imbalance problem …
different classes varies dramatically, which leads to a severe class imbalance problem …
Deep metric learning assisted by intra-variance in a semi-supervised view of learning
P Liu, Z Liu, Y Lang, S Liu, Q Zhou, Q Li - Engineering Applications of …, 2024 - Elsevier
Deep metric learning aims to construct an embedding space where samples belonging to
the same class are closely grouped together, while samples from different classes are …
the same class are closely grouped together, while samples from different classes are …
Unsupervised balanced hash codes learning with multichannel feature fusion
Unsupervised hashingalgorithms are widely used in large-scale remote sensing images
(RSIs) retrieval task. However, existing RSI retrieval algorithms fail to capture the …
(RSIs) retrieval task. However, existing RSI retrieval algorithms fail to capture the …
Composed Image Retrieval for Remote Sensing
This work introduces composed image retrieval to remote sensing. It allows to query a large
image archive by image examples alternated by a textual description, enriching the …
image archive by image examples alternated by a textual description, enriching the …
Unsupervised Transformer Balanced Hashing for Multispectral Remote Sensing Image Retrieval
For remote sensing (RS) image retrieval task, hashing technology have been extensively
researched in recent works. Unsupervised hashing approaches have attracted much …
researched in recent works. Unsupervised hashing approaches have attracted much …
Query by Example in Remote Sensing Image Archive Using Enhanced Deep Support Vector Data Description
O Ghozatlou, MH Conde… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
This article studies remote sensing image retrieval using kernel-based support vector data
description (SVDD). We exploit deep SVDD, which is a well-known method for one-class …
description (SVDD). We exploit deep SVDD, which is a well-known method for one-class …
Combining Deep Metric Learning Approaches for Aerial Scene Classification
FA Faria, LH Buris, FAM Cappabianco… - arXiv preprint arXiv …, 2023 - arxiv.org
Aerial scene classification, which aims to semantically label remote sensing images in a set
of predefined classes (eg, agricultural, beach, and harbor), is a very challenging task in …
of predefined classes (eg, agricultural, beach, and harbor), is a very challenging task in …