Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Cui, Kangning"'
Autor:
Cui, Kangning, Tang, Wei, Zhu, Rongkun, Wang, Manqi, Larsen, Gregory D., Pauca, Victor P., Alqahtani, Sarra, Yang, Fan, Segurado, David, Fine, Paul, Karubian, Jordan, Chan, Raymond H., Plemmons, Robert J., Morel, Jean-Michel, Silman, Miles R.
Understanding the spatial distribution of palms within tropical forests is essential for effective ecological monitoring, conservation strategies, and the sustainable integration of natural forest products into local and global supply chains. However
Externí odkaz:
http://arxiv.org/abs/2410.11124
Autor:
Cui, Kangning, Shao, Zishan, Larsen, Gregory, Pauca, Victor, Alqahtani, Sarra, Segurado, David, Pinheiro, João, Wang, Manqi, Lutz, David, Plemmons, Robert, Silman, Miles
Palms play an outsized role in tropical forests and are important resources for humans and wildlife. A central question in tropical ecosystems is understanding palm distribution and abundance. However, accurately identifying and localizing palms in g
Externí odkaz:
http://arxiv.org/abs/2403.03161
Autor:
Cui, Kangning, Li, Ruoning, Polk, Sam L., Lin, Yinyi, Zhang, Hongsheng, Murphy, James M., Plemmons, Robert J., Chan, Raymond H.
Hyperspectral images (HSIs) provide exceptional spatial and spectral resolution of a scene, crucial for various remote sensing applications. However, the high dimensionality, presence of noise and outliers, and the need for precise labels of HSIs pre
Externí odkaz:
http://arxiv.org/abs/2312.15447
Diabetic retinopathy (DR) is a leading global cause of blindness. Early detection of hard exudates plays a crucial role in identifying DR, which aids in treating diabetes and preventing vision loss. However, the unique characteristics of hard exudate
Externí odkaz:
http://arxiv.org/abs/2302.11517
Autor:
Pan, Fei, Wu, Yutong, Cui, Kangning, Chen, Shuxun, Li, Yanfang, Liu, Yaofang, Shakoor, Adnan, Zhao, Han, Lu, Beijia, Zhi, Shaohua, Chan, Raymond, Sun, Dong
Despite recent advances in data-independent and deep-learning algorithms, unstained live adherent cell instance segmentation remains a long-standing challenge in cell image processing. Adherent cells' inherent visual characteristics, such as low cont
Externí odkaz:
http://arxiv.org/abs/2301.11499
Autor:
Cui, Kangning, Camalan, Seda, Li, Ruoning, Pauca, Victor P., Alqahtani, Sarra, Plemmons, Robert J., Silman, Miles, Dethier, Evan N., Lutz, David, Chan, Raymond H.
Artisanal and Small-scale Gold Mining (ASGM) is an important source of income for many households, but it can have large social and environmental effects, especially in rainforests of developing countries. The Sentinel-2 satellites collect multispect
Externí odkaz:
http://arxiv.org/abs/2206.09365
Autor:
Cui, Kangning, Li, Ruoning, Polk, Sam L., Murphy, James M., Plemmons, Robert J., Chan, Raymond H.
Hyperspectral images, which store a hundred or more spectral bands of reflectance, have become an important data source in natural and social sciences. Hyperspectral images are often generated in large quantities at a relatively coarse spatial resolu
Externí odkaz:
http://arxiv.org/abs/2204.13497
Autor:
Polk, Sam L., Chan, Aland H. Y., Cui, Kangning, Plemmons, Robert J., Coomes, David A., Murphy, James M.
Ash dieback (Hymenoscyphus fraxineus) is an introduced fungal disease that is causing the widespread death of ash trees across Europe. Remote sensing hyperspectral images encode rich structure that has been exploited for the detection of dieback dise
Externí odkaz:
http://arxiv.org/abs/2204.09041
Hyperspectral images encode rich structure that can be exploited for material discrimination by machine learning algorithms. This article introduces the Active Diffusion and VCA-Assisted Image Segmentation (ADVIS) for active material discrimination.
Externí odkaz:
http://arxiv.org/abs/2204.06298
In this work, a novel algorithm called SVM with Shape-adaptive Reconstruction and Smoothed Total Variation (SaR-SVM-STV) is introduced to classify hyperspectral images, which makes full use of spatial and spectral information. The Shape-adaptive Reco
Externí odkaz:
http://arxiv.org/abs/2203.15619