Semantic image segmentation: Two decades of research
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …
vision applications, providing key information for the global understanding of an image. This …
Unsupervised domain adaptation for semantic image segmentation: a comprehensive survey
Semantic segmentation plays a fundamental role in a broad variety of computer vision
applications, providing key information for the global understanding of an image. Yet, the …
applications, providing key information for the global understanding of an image. Yet, the …
Unsupervised person re-identification in aerial imagery
The rapidly increasing use of unmanned aerial vehicles (UAVs) for surveillance has paved
the way for advanced image analysis techniques to enhance public safety. Among many …
the way for advanced image analysis techniques to enhance public safety. Among many …
Segmentation of farmlands in aerial images by deep learning framework with feature fusion and context aggregation modules
Automated segmentation of farmland patterns in high resolution aerial images is very crucial
for smart farming. Recently, deep learning techniques have achieved tremendous success …
for smart farming. Recently, deep learning techniques have achieved tremendous success …
Fine-Tuning Network in Federated Learning for Personalized Skin Diagnosis
Federated learning (FL) has emerged as a promising technique in the field of medical
diagnosis. By distributing the same task through deep networks on mobile devices, FL has …
diagnosis. By distributing the same task through deep networks on mobile devices, FL has …
Building extraction from remote sensing images with deep learning: A survey on vision techniques
Y Yuan, X Shi, J Gao - Computer Vision and Image Understanding, 2024 - Elsevier
Building extraction from remote sensing images is a hot topic in the fields of computer vision
and remote sensing. In recent years, driven by deep learning, the accuracy of building …
and remote sensing. In recent years, driven by deep learning, the accuracy of building …
Learning to generalize aerial person re‐identification using the meta‐transfer method
L Xu, H Peng, X Lu, D Xia - Concurrency and Computation …, 2023 - Wiley Online Library
Person re‐identification (Re‐ID) aims to retrieve a person of interest across multiple
nonoverlapping cameras. In recent years, to enable person Re‐ID technology to play out its …
nonoverlapping cameras. In recent years, to enable person Re‐ID technology to play out its …
Parameter instance learning with enhanced vision transformers for aerial person re‐identification
H Peng, X Lu, L Xu, D Xia, X Xie - … and Computation: Practice …, 2024 - Wiley Online Library
In an agnostic space environment, aerial person re‐identification (Re‐ID) is a task that the
query person may not occur in the gallery set, it is considered a subordinate task within the …
query person may not occur in the gallery set, it is considered a subordinate task within the …
Meta-transfer learning for person re-identification in aerial imagery
L Xu, H Peng, L Wang, D Xia - CCF Conference on Computer Supported …, 2022 - Springer
Person re-identification (Re-ID) aims to retrieve a person of interest across multiple
nonoverlapping cameras. In the last few years, the construction of aerial person Re-ID …
nonoverlapping cameras. In the last few years, the construction of aerial person Re-ID …
Learning Self-Supervised Vision Transformers from Scratch for Aerial Person Re-Identification
H Peng, L Xu, X Lu, D Xia - 2023 13th International Conference …, 2023 - ieeexplore.ieee.org
In recent years, person re-identification (Re-ID) as a widely studied computer vision task,
has reached a saturation state under closed-world setting, which encourages researchers to …
has reached a saturation state under closed-world setting, which encourages researchers to …