Indrajit Kalita
Orcid: 0000-0002-2854-0709
According to our database1,
Indrajit Kalita
authored at least 11 papers
between 2019 and 2024.
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Bibliography
2024
A deep learning-based technique for firm classification and domain adaptation in land cover classification using time-series aerial images.
Earth Sci. Informatics, February, 2024
2023
Class-Wise Subspace Alignment-Based Unsupervised Adaptive Land Cover Classification in Scene-Level Using Deep Siamese Network.
IEEE Trans. Neural Networks Learn. Syst., July, 2023
Crop classification using aerial images by analyzing an ensemble of DCNNs under multi-filter & multi-scale framework.
Multim. Tools Appl., May, 2023
2022
Deep Learning-Based Cross-Sensor Domain Adaptation Under Active Learning for Land Cover Classification.
IEEE Geosci. Remote. Sens. Lett., 2022
Inception time DCNN for land cover classification by analyzing multi-temporal remotely sensed images.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Unsupervised cross-sensor domain adaptation using adversarial network for land cover classification.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
2021
Land Use Change Detection Using Deep Siamese Neural Networks and Weakly Supervised Learning.
Proceedings of the Computer Analysis of Images and Patterns, 2021
2020
Deep Neural Network-Based Heterogeneous Domain Adaptation Using Ensemble Decision Making in Land Cover Classification.
IEEE Trans. Artif. Intell., 2020
2019
Unsupervised domain adaptation in land-cover classification under neural approach using feature-level ensemble.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
An Adversarial Learning Mechanism for Dealing with the Class-Imbalance Problem in Land-Cover Classification.
Proceedings of the Hybrid Intelligent Systems, 2019
Deep Ensemble Network for Handling Class-Imbalance Problem in Land-Cover Classification.
Proceedings of the 2019 International Conference on Information Technology (ICIT), 2019