2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IP-6.5
Paper Title IR-SSL: IMPROVED REGULARIZATION BASED SEMI-SUPERVISED LEARNING FOR LAND COVER CLASSIFICATION
Authors Habib Ullah, University of Ha'il, Saudi Arabia, Saudi Arabia; Tawsin Uddin Ahmed, Mohib Ullah, Faouzi Alaya Cheikh, Norwegian University of Science and Technology, Norway
SessionMLR-APPL-IP-6: Machine learning for image processing 6
LocationArea E
Session Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image processing
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Abstract Land cover classification has significant contributions in several applications including natural calamities estimation and response, observation of environmental changes, and urban planning to name a few. These types of applications demand the identification of different categories of land cover. Traditional land cover classification is significantly dependent on the availability of huge amount of labeled data. However, labeling satellite data is very time consuming and it often requires expert knowledge. To alleviate the dependency on labeled data, we propose a novel and improved regularization based deep semi-supervised learning (IR-SSL) method for land cover classification. Adaptation of deep semi-supervised learning approach in such a task gains reliability due to its robustness in feature learning. To consolidate the performance of our deep semi-supervised learning method, we combine it with a robust data augmentation technique. We perform experiments on a benchmark dataset. Considering limited labeled samples from the dataset, our method outperforms many state-of-the-art models.