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A multi-scale weakly supervised learning method with adaptive online noise correction for high-resolution change detection of built-up areas
Accurate change detection of built-up areas (BAs) fosters a comprehensive understanding of
urban development. The post-classification comparison (PCC) is a widely-used change …
urban development. The post-classification comparison (PCC) is a widely-used change …
A weakly supervised learning framework for salient object detection via hybrid labels
Fully-supervised salient object detection (SOD) methods have made great progress, but
such methods often rely on a large number of pixel-level annotations, which are time …
such methods often rely on a large number of pixel-level annotations, which are time …
Zoomnext: A unified collaborative pyramid network for camouflaged object detection
Recent camouflaged object detection (COD) attempts to segment objects visually blended
into their surroundings, which is extremely complex and difficult in real-world scenarios …
into their surroundings, which is extremely complex and difficult in real-world scenarios …
Tcnet: Co-salient object detection via parallel interaction of transformers and cnns
Y Ge, Q Zhang, TZ **ang, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The purpose of co-salient object detection (CoSOD) is to detect the salient objects that co-
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
Collaborative camouflaged object detection: A large-scale dataset and benchmark
C Zhang, H Bi, TZ **ang, R Wu, J Tong… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
In this article, we provide a comprehensive study of a new task called collaborative
camouflaged object detection (CoCOD), which aims to simultaneously detect camouflaged …
camouflaged object detection (CoCOD), which aims to simultaneously detect camouflaged …
Global–local–global context-aware network for salient object detection in optical remote sensing images
For the salient object detection in optical remote sensing images (ORSI-SOD), many existing
methods are trapped in a local–global mode, ie, CNN-based encoder binds with a specific …
methods are trapped in a local–global mode, ie, CNN-based encoder binds with a specific …
[HTML][HTML] A novel weakly-supervised method based on the segment anything model for seamless transition from classification to segmentation: A case study in …
In the quest for large-scale photovoltaic (PV) panel extraction, substantial data volumes are
essential, given the demand for sub-meter rooftop PV resolution. This requires the concept …
essential, given the demand for sub-meter rooftop PV resolution. This requires the concept …
Improved camouflaged detection in the large-scale images and videos with minimum boundary contrast in detection technique
Z Xu, J Wang, F Hu, G Abbas, E Touti… - Expert Systems with …, 2024 - Elsevier
Recognizing camouflaged items in large-scale images or movies is a complex challenge
requiring close attention to detail present here. These items have no discernible edges and …
requiring close attention to detail present here. These items have no discernible edges and …
A unified query-based paradigm for camouflaged instance segmentation
Due to the high similarity between camouflaged instances and the background, the recently
proposed camouflaged instance segmentation (CIS) faces challenges in accurate …
proposed camouflaged instance segmentation (CIS) faces challenges in accurate …
Localization, balance and affinity: a stronger multifaceted collaborative salient object detector in remote sensing images
Despite significant advancements in salient object detection (SOD) in optical remote sensing
images (ORSIs), challenges persist due to the intricate edge structures of ORSIs and the …
images (ORSIs), challenges persist due to the intricate edge structures of ORSIs and the …