Results 261 to 270 of about 4,979,837 (328)

Quantum reservoir computing for photonic entanglement witnessing. [PDF]

Sci Adv
Zia D, Innocenti L, Minati G, Lorenzo S, Suprano A, Di Bartolo R, Spagnolo N, Giordani T, Cimini V, Palma GM, Ferraro A, Sciarrino F, Paternostro M.   +12 more
europepmc   +1 more source

Diffraction perception in L-shaped rooms using virtual reality. [PDF]

EURASIP J Audio Speech Music Process
Mannall J, Neidhardt A, Calamia P, Savioja L, Mason R, De Sena E.   +5 more
europepmc   +1 more source

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Shadow Detection via Predicting the Confidence Maps of Shadow Detection Methods

Proceedings of the 29th ACM International Conference on Multimedia, 2021
Today's mainstream shadow detection methods are manually designed via a case-by-case approach. Accordingly, these methods may only be able to detect shadows for specific scenes. Given the complex and diverse shadow scenes in reality, none of the existing methods can provide a one-size-fits-all solution with satisfactory performance.
Jingwei Liao, Yanli Liu, Guanyu Xing, Housheng Wei, Jueyu Chen, Songhua Xu   +5 more
openaire   +2 more sources

Robust Shadow Detection by Exploring Effective Shadow Contexts

Proceedings of the 29th ACM International Conference on Multimedia, 2021
Effective contexts for separating shadows from non-shadow objects can appear in different scales due to different object sizes. This paper introduces a new module, Effective-Context Augmentation (ECA), to utilize these contexts for robust shadow detection with deep structures.
Xianyong Fang, Xiaohao He, Linbo Wang, Jianbing Shen   +3 more
openaire   +2 more sources

Distraction-Aware Shadow Detection

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Shadow detection is an important and challenging task for scene understanding. Despite promising results from recent deep learning based methods. Existing works still struggle with ambiguous cases where the visual appearances of shadow and non-shadow regions are similar (referred to as distraction in our context).
Quanlong Zheng, Xiaotian Qiao, Ying Cao, Rynson W.H. Lau   +3 more
openaire   +2 more sources

Object-based cloud and cloud shadow detection in Landsat imagery

Remote Sensing of Environment, 2012
Zhe Zhu, C. Woodcock
semanticscholar   +3 more sources

Deeply supervised convolutional neural network for shadow detection based on a novel aerial shadow imagery dataset

ISPRS Journal of Photogrammetry and Remote Sensing, 2020
Shadow detection is an essential work for remote sensing image analysis, as the presence of shadows in high resolution images not only degrades the radiometric information but also disturbs the image interpretation.
Shuang Luo, Huifang Li, Huanfeng Shen
semanticscholar   +3 more sources

Shadow Detection on High-Resolution Digital Orthophoto Map Using Semantic Matching

IEEE Transactions on Geoscience and Remote Sensing, 2023
Shadow detection and compensation on high-resolution orthophoto is one of the most important tasks for ensuring the high quality of the radiometric balance of a digital orthophoto map (DOM).
Guoqing Zhou, Yi Tang, Wen-Xin Zhang, Weiguang Liu, Yue Jiang, E. Gao, Qiang Zhu, Yuhang Bai   +7 more
semanticscholar   +1 more source

Make Segment Anything Model Perfect on Shadow Detection

IEEE Transactions on Geoscience and Remote Sensing, 2023
Compared to models pretrained on ImageNet, the segment anything model (SAM) has been trained on a massive segmentation corpus, excelling in both generalization ability and boundary localization.
Xiao-diao Chen, Wen Wu, Wenyang Yang, Hongshuai Qin, Xiantao Wu, Xiaoyang Mao   +5 more
semanticscholar   +1 more source