Results 231 to 240 of about 12,080 (258)

ERS-2 SAR image analysis for sea ice classification in the marginal ice zone

IEEE International Geoscience and Remote Sensing Symposium, 2003
The possibility to distinguish between different sea ice types in the marginal ice zone in the Greenland Sea using ERS-2 SAR is investigated. Statistical, textural and spectral features derived from ERS-2 SAR images and ice concentrations from 85 GHz SSM/I data are analyzed using learning vector quantization. The proposed method is useful for resolving
Lars Kaleschke, Stefan Kern
openaire   +1 more source

Classification of Baltic Sea ice with airborne microwave radiometer

Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium, 2002
A helicopter-borne multifrequency radiometer (24, 34, 48 and 94 GHz, vertical polarization) was used to investigate the behaviour of the brightness temperature of different sea ice types in the northern Baltic Sea. The measurements were made in dry and wet conditions (air temperature above and below 0/spl deg/C).
L. Kurvonen, M. Toikka, M. Hallikainen
openaire   +1 more source

Sea Ice Classification Using Mutually Guided Contexts

IEEE Transactions on Geoscience and Remote Sensing, 2023
Xiaoyu Sun 0009, Xi Zhang, Weimin Huang 0001, Zongjun Han, Xinrong Lyu, Peng Ren 0001   +5 more
openaire   +1 more source

Machine learning techniques for sea-ice identification and classification

2023
Sea-ice identification and classification are essential processes for safety critical navigation support of surface vessels in polar waters. Semantic segmentation has drawn much attention as an enabling technique for fast detection of objects in a scene including sea-ice conditions.
openaire   +1 more source

A dynamic local thresholding technique for sea ice classification

Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium, 2002
Many methods of sea ice classification are based upon global thresholding techniques. In thresholding, points are selected according to the histogram of an image and are used to achieve a representation of that image in a limited number of gray levels, or classifications. The authors have developed and implemented a local thresholding technique adapted
D. Haverkamp, L.K. Soh, C. Tsatsoulis
openaire   +1 more source

Automatic Sea-Ice Classification of SAR Images Based on Spatial and Temporal Features Learning

IEEE Transactions on Geoscience and Remote Sensing, 2021
Zhenling Ma, Wei Song, Cristian Perra
exaly  

Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data

Remote Sensing, 2021
Xiao-Ming Li, Xiao Cheng, Mohammed Shokr   +2 more
exaly  

Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification

Remote Sensing, 2021
Wolfgang Dierking, Johannes Lohse, Anthony Doulgeris   +2 more
exaly  

Landsat-8 Sea Ice Classification Using Deep Neural Networks

Remote Sensing, 2022
Wiebke Aldenhoff, Egbert Schwarz
exaly  

Spaceborne GNSS-R for Sea Ice Classification Using Machine Learning Classifiers

Remote Sensing, 2021
Kegen Yu, Li Shuiping, Maximilian Semmling   +2 more
exaly