Ghent University Academic Bibliography

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Detecting and characterizing corrosion on high voltage metallic towers using hyperspectral imaging

Zohreh Zahiri, Hiep Luong (UGent) , Ljiljana Platisa (UGent) , Roeland Vandebriel, Murali Jayapala, Frédéric Mangialetto and Paul Scheunders

(2022) 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Abstracts.
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- Book Editor
Advanced concepts for intelligent vision systems - ACIVS 2020

Jacques Blanc-Talon, Patrice Delmas, Wilfried Philips (UGent) , Dan Popescu and Paul Scheunders

(2020) In Image Processing, Computer Vision, Pattern Recognition, and Graphics 12002.
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- Journal Article
- A1
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Decision fusion framework for hyperspectral image classification based on Markov and conditional random fields

Vera Andrejchenko, Wenzhi Liao (UGent) , Wilfried Philips (UGent) and Paul Scheunders

(2019) REMOTE SENSING. 11(6).
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Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform

Mohd Shahrimie Mohd Asaari, Stien Mertens (UGent) , Stijn Dhondt (UGent) , Dirk Inzé (UGent) , Nathalie Wuyts (UGent) and Paul Scheunders

(2019) COMPUTERS AND ELECTRONICS IN AGRICULTURE. 162. p.749-758
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MRF-based decision fusion for hyperspectral image classification

Vera Andrejchenko, Rob Heylen, Wenzhi Liao (UGent) , Wilfried Philips (UGent) and Paul Scheunders

(2018) IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM. p.8066-8069
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Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

Mohd Shahrimie Mohd Asaari, Puneet Mishra, Stien Mertens (UGent) , Stijn Dhondt (UGent) , Dirk Inzé (UGent) , Nathalie Wuyts (UGent) and Paul Scheunders

(2018) ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING. 138. p.121-138
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- open access
Advanced concepts for intelligent vision systems, 19th international conference, ACIVS 2018, proceedings

Jacques Blanc-Talon, David Helbert, Wilfried Philips (UGent) , Dan Popescu and Paul Scheunders

(2018) In Lecture Notes in Computer Science 11182.
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Fusion of hyperspectral and LiDAR data for classification of cloud-shadow mixed remote sensed scene

Renbo Luo (UGent) , Wenzhi Liao (UGent) , Hongyan Zhang, Liangpei Zhang, Paul Scheunders, Youguo Pi and Wilfried Philips (UGent)

(2017) IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. 10(8). p.3768-3781
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Advanced concepts for intelligent vision systems : 18th International Conference, ACIVS 2017, Antwerp, Belgium, September 18-21, 2017, Proceedings

Jacques Blanc-Talon, Rudi Penne, Wilfried Philips (UGent) , Dan Popescu and Paul Scheunders

(2017) In Lecture Notes in Computer Science 10617.
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- Miscellaneous
Classification of hyperspectral images with very small training size using sparse unmixing

Vera Andrejchenko, Rob Heylen, Paul Scheunders, Wilfried Philips (UGent) and Wenzhi Liao (UGent)

(2016) 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

Academic Bibliography

Detecting and characterizing corrosion on high voltage metallic towers using hyperspectral imaging

Advanced concepts for intelligent vision systems - ACIVS 2020

Decision fusion framework for hyperspectral image classification based on Markov and conditional random fields

Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform

MRF-based decision fusion for hyperspectral image classification

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

Advanced concepts for intelligent vision systems, 19th international conference, ACIVS 2018, proceedings

Fusion of hyperspectral and LiDAR data for classification of cloud-shadow mixed remote sensed scene

Advanced concepts for intelligent vision systems : 18th International Conference, ACIVS 2017, Antwerp, Belgium, September 18-21, 2017, Proceedings

Classification of hyperspectral images with very small training size using sparse unmixing

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